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  • 1.
    Aler Tubella, Andrea
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Theodorou, Andreas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Governance by glass-box: implementing transparent moral bounds for AI behaviour2019In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019, p. 5787-5793Conference paper (Other academic)
    Abstract [en]

    Artificial Intelligence (AI) applications are being used to predict and assess behaviour in multiple domains which directly affect human well-being. However, if AI is to improve people’s lives, then people must be able to trust it, by being able to understand what the system is doing and why. Although transparency is often seen as the requirementin this case, realistically it might not always be possible, whereas the need to ensure that the system operates within set moral bounds remains.

    In this paper, we present an approach to evaluate the moral bounds of an AI system based on the monitoring of its inputs and outputs. We place a ‘Glass-Box’ around the system by mapping moral values into explicit verifiable norms that constrain inputs and outputs, in such a way that if these remain within the box we can guarantee that the system adheres to the value. The focus on inputs and outputs allows for the verification and comparison of vastly different intelligent systems; from deep neural networks to agent-based systems.

    The explicit transformation of abstract moral values into concrete norms brings great benefits interms of explainability; stakeholders know exactly how the system is interpreting and employing relevant abstract moral human values and calibrate their trust accordingly. Moreover, by operating at a higher level we can check the compliance of the system with different interpretations of the same value.

  • 2.
    Ansari, Saba Gholizadeh
    et al.
    Utrecht University, Utrecht, Netherlands.
    Prasetya, I.S.W.B.
    Utrecht University, Utrecht, Netherlands.
    Dastani, Mehdi
    Utrecht University, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Keller, Gabriele
    Utrecht University, Utrecht, Netherlands.
    An appraisal transition system for event-driven emotions in agent-based player experience testing2022In: Engineering multi-agent systems / [ed] Natasha Alechina; Matteo Baldoni; Brian Logan, Springer, 2022, p. 156-174Conference paper (Refereed)
    Abstract [en]

    Player experience (PX) evaluation has become a field of interest in the game industry. Several manual PX techniques have been introduced to assist developers to understand and evaluate the experience of players in computer games. However, automated testing of player experience still needs to be addressed. An automated player experience testing framework would allow designers to evaluate the PX requirements in the early development stages without the necessity of participating human players. In this paper, we propose an automated player experience testing approach by suggesting a formal model of event-based emotions. In particular, we discuss an event-based transition system to formalize relevant emotions using Ortony, Clore, & Collins (OCC) theory of emotions. A working prototype of the model is integrated on top of Aplib, a tactical agent programming library, to create intelligent PX test agents, capable of appraising emotions in a 3D game case study. The results are graphically shown e.g. as heat maps. Visualization of the test agent’s emotions would ultimately help game designers to produce contents that evoke a certain experience in players.

  • 3.
    Ansari, Saba Gholizadeh
    et al.
    Utrecht University, Utrecht, Netherlands.
    Prasetya, I.S.W.B.
    Utrecht University, Utrecht, Netherlands.
    Prandi, Davide
    Fondazione Bruno Kessler, Trento, Italy.
    Kifetew, Fitsum Meshesha
    Fondazione Bruno Kessler, Trento, Italy.
    Dastani, Mehdi
    Utrecht University, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Keller, Gabriele
    Utrecht University, Utrecht, Netherlands.
    Model-based player experience testing with emotion pattern verification2023In: Fundamental approaches to software engineering: 26th international conference, FASE 2023, held as part of the European joint Conferences on theory and practice of software, ETAPS 2023, Paris, France, April 22–27, 2023, Proceedings / [ed] Leen Lambers; Sebastián Uchitel, Springer Science+Business Media B.V., 2023, p. 151-172Conference paper (Refereed)
    Abstract [en]

    Player eXperience (PX) testing has attracted attention in the game industry as video games become more complex and widespread. Understanding players’ desires and their experience are key elements to guarantee the success of a game in the highly competitive market. Although a number of techniques have been introduced to measure the emotional aspect of the experience, automated testing of player experience still needs to be explored. This paper presents a framework for automated player experience testing by formulating emotion patterns’ requirements and utilizing a computational model of players’ emotions developed based on a psychological theory of emotions along with a model-based testing approach for test suite generation. We evaluate the strength of our framework by performing mutation test. The paper also evaluates the performance of a search-based generated test suite and LTL model checking-based test suite in revealing various variations of temporal and spatial emotion patterns. Results show the contribution of both algorithms in generating complementary test cases for revealing various emotions in different locations of a game level.

  • 4.
    Baum, Kevin
    et al.
    Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) and Algoright, Kaiserslautern, Germany.
    Bryson, Joanna
    Hertie School, Berlin, Germany.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Grobelnik, Marko
    OECD, Paris, France.
    Hoos, Holger
    Aachen University, Aachen, Germany.
    Irgens, Morten
    CLAIRE-AI.org, Oslo Metropolitan Universit, Oslo, Norway.
    Lukowicz, Paul
    Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI), Kaiserslautern, Germany.
    Muller, Catelijne
    ALLAI, Amsterdam, Netherlands.
    Rossi, Francesca
    IBM, NY, Yorktown, United States.
    Shawe-Taylor, John
    IRCAI, International Research Institute on AI, Ljubljana, Slovenia.
    Theodorou, Andreas
    VerAI.
    Vinuesa, Ricardo
    KTH Royal Institute of Technology, Stockholm, Sweden.
    From fear to action: AI governance and opportunities for all2023In: Frontiers in Computer Science, E-ISSN 2624-9898, Vol. 5, article id 1210421Article in journal (Other academic)
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  • 5.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Increasing robot understandability through social practices2022In: Proceedings of Cultu-Ro 2022, Workshop on Cultural Influences in Human-Robot Interaction: Today and Tomorrow: 31st IEEE International Conference on Robot and Human Interactive Communication (Ro-Man 22), 2022Conference paper (Refereed)
    Abstract [en]

    In this short paper we discuss how incorporatingsocial practices in robotics may contribute to how well humansunderstand robots’ actions and intentions. Since social practicestypically are applied by all interacting parties, also the robots’understanding of the humans may improve.We further discuss how the involved mechanisms have to beadjusted to fit the cultural context in which the interaction takesplace, and how social practices may have to be transformed tofit a robot’s capabilities and limitations.

  • 6. Boshuijzen-van Burken, Christine
    et al.
    Gore, Ross
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Royakkers, Lamber
    Wozny, Phillip
    Shults, F. Leron
    Agent-Based Modelling of Values: The Case of Value Sensitive Design for Refugee Logistics2020In: JASSS: Journal of Artificial Societies and Social Simulation, E-ISSN 1460-7425, Vol. 23, no 4, article id 6Article in journal (Refereed)
    Abstract [en]

    We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz's theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different 'value-scenarios', stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform (interactive website) for decision-makers to understand the trade-offs in policies for government and non-government organizations.

    Download full text (pdf)
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  • 7.
    Clodic, Aurélie
    et al.
    LAAS-CNRS, Université de Toulouse, France.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Fernández Castro, Víctor
    LAAS-CNRS, Université de Toulouse, France; Institut Jean Nicod, Cnrs Umr 8129, DEC, ENS, Psl University, France.
    Hakli, Raul
    Department of Practical Philosophy, University of Helsinki, Finland.
    Social Models for Social Robotics2020In: Culturally Sustainable Social Robotics / [ed] Marco Nørskov, Johanna Seibt, Oliver Santiago Quick, IOS Press, 2020, p. 515-519Conference paper (Refereed)
    Abstract [en]

    Social robotics is one of the most important emerging technologies, with potentially profound socio-cultural impact. However, the current interdisciplinary research areas of 'social robotics' and 'Human-Robot Interaction' (HRI) are not yet equipped with the necessary conceptual tools in order to design interactions between humans and robots. New approaches for effective yet context-adequate social interactions are needed, that observe overarching ethical principles and take larger socio-cultural perspectives into account. With this workshop, we aim to clarify questions arising with this new technology. How far can robots go-now and in the future-to fulfill the requirements of full-blown social agents? How and where do ethical requirements dovetail with the elements (conditions, principles, and procedures) for social agency? This workshop will be part of the 'Toward a Framework for Joint Action' series (fja.sciencesconf.org).

  • 8.
    Cranefield, Stephen
    et al.
    University of Otago, Dunedin, New Zealand.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Czech University of Technology in Prague, Prague, Czech Republic; Utrecht University, Utrecht, Netherlands.
    Incorporating social practices in BDI agent systems2020In: Engineering multi-agent systems: 7th International Workshop, EMAS 2019, Montreal, QC, Canada, May 13–14, 2019, Revised Selected Papers / [ed] Louise A. Dennis; Rafael H. Bordini; Yves Lespérance, Springer, 2020, p. 109-126Conference paper (Refereed)
    Abstract [en]

    When agents interact with humans, either through embodied agents or because they are embedded in a robot, it would be easy if they could use fixed interaction protocols as they do with other agents. However, people do not keep fixed protocols in their day-to-day interactions and the social environment is often dynamic, making it impossible to use fixed protocols. Deliberating about interactions from fundamentals is not very scalable either, because in that case all possible reactions of a human have to be considered in the agent’s plans. In this paper we argue that social practices can be used as an inspiration for designing flexible and scalable interaction mechanisms that are also robust. However, using social practices requires extending the traditional BDI deliberation cycle to monitor landmark states and perform expected actions by leveraging existing plans. We define and implement this mechanism in Jason using a periodically run meta-deliberation plan, supported by a metainterpreter, and illustrate its use in a realistic scenario.

  • 9.
    Cranefield, Stephen
    et al.
    University of Otago, Dunedin, New Zealand.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Incorporating social practices in BDI agent systems2019In: AAMAS '19: Proceedings of the 18th international conference on autonomous agents and multiagent systems, International Foundation for Autonomous Agents and Multiagent System , 2019, p. 1901-1903Conference paper (Refereed)
  • 10.
    den Hurk, Mijke van
    et al.
    Utrecht University, Utrecht, Netherlands; Dutch National Police, The Hague, Netherlands.
    Dechesne, Mark
    Universiteit Leiden, Leiden, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands; CVUT Prague, Prague, Czech Republic.
    First step towards a new understanding of radicalisation: modeling identity fusion2023In: Advances in social simulation: Proceedings of the 17th Social Simulation Conference, European Social Simulation Association / [ed] Flaminio Squazzoni, Springer Nature, 2023, p. 223-234Conference paper (Refereed)
    Abstract [en]

    We want to understand in which circumstances identity fusion occurs. We propose a model in which individual needs and interactions between agents and their social environment come together. We argue the personal identity of an agent will fuse with a group when it has a high need for significance and he is member of a group providing a means to gain significance. Agents cannot join all groups to meet their needs, as agents need to have a social connection with the group and need to be accepted within the group. The model allows for multiple scenarios to occur. Agents with a need for significance not necessarily become fused and will find alternative ways to satisfy their need.

  • 11.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Should we make predictions based on social simulations?2023In: International Journal of Social Research Methodology, ISSN 1364-5579, E-ISSN 1464-5300, Vol. 26, no 2, p. 193-206Article in journal (Refereed)
    Abstract [en]

    The general feeling is that no predictions can be made based on agent-based social simulations. The outcomes of social simulations are based on the behaviors of individuals and their interactions. Behavioral models are always incomplete and often, also incorrect with respect to real behavior and thus the outcomes of agent-based social simulations cannot be trusted as predictions. In this article, we argue that behavioral models do not have to be valid in all respects, but only in the essential aspects in order to be able to make useful predictions. Based on some case studies on the effectiveness of restrictions during the COVID-19 crisis, we show that what are essential aspects of a behavioral model that need to be valid depends on the specific situation that is simulated. The predictions that were needed for the COVID-19 crisis were made with an agent-based social simulation framework using a behavioral model based on needs. The predictions could indicate the relative increase or decrease of COVID-19 infections due to the introduction of a new restriction. It shows that useful predictions can be made based on social simulations, but that we have to be careful on what type of predictions to make.

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  • 12.
    Dignum, Frank
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Corchado, Juan Manuel
    Universidad de Salamanca, Salamanca, Salamanca, Spain.
    De la Prieta, Fernando
    University of Salamanca, Salamanca, Spain.
    Preface2021In: International Conference on Practical Applications of Agents and Multi-Agent Systems, ISSN 03029743Article in journal (Other academic)
  • 13.
    Dignum, Frank
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    How to center AI on humans2020In: NeHuAI 2020. First International Workshop on New Foundations for Human-Centered AI: Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI)co-located with 24th European Conference on Artificial Intelligence (ECAI 2020) / [ed] Alessandro Saffiotti; Luciano Serafini; Paul Lukowicz, 2020, p. 59-62Conference paper (Refereed)
    Abstract [en]

    In this position paper we investigate what it means for AI to be human-centered. Although many organisations and researchers by now have given requirements for human-centeredness, such as: transparancy, respect for human autonomy, fairness and accountability, this does little to indicate how the AI techniques should be designed in order to be human-centered. In this paper we argue that human-centered AI involves a shift from AI emulating intelligent human tasks, to emulating human intelligence such that we capture enough social intelligence in order for the AI system to be able to center its activity and reasoning on its human users.

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  • 14.
    Dignum, Frank
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Davidsson, Paul
    Ghorbani, Amineh
    van der Hurk, Mijke
    Jensen, Maarten
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kammler, Christian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Lorig, Fabian
    Ludescher, Luis Gustavo
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Melchior, Alexander
    Mellema, Rene
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Pastrav, Cezara
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Vanhee, Lois
    Verhagen, Harko
    Analysing the Combined Health, Social and Economic Impacts of the Corovanvirus Pandemic Using Agent-Based Social Simulation2020In: Minds and Machines, ISSN 0924-6495, E-ISSN 1572-8641, Vol. 30, no 2, p. 177-194Article in journal (Refereed)
    Abstract [en]

    During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions.

  • 15.
    Dignum, Frank
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Mathieu, PhilippeUniversity of Lille, Lille, France.Corchado, Juan ManuelUniversity of Salamanca, Salamanca, Spain; AIR Institute, Salamanca, Spain.De La Prieta, FernandoUniversity of Salamanca, Salamanca, Spain.
    Advances in practical applications of agents, multi-agent systems, and complex systems simulation: the PAAMS collection2022Conference proceedings (editor) (Other academic)
  • 16.
    Dignum, Frank
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Mathieu, Philippe
    University of Lille, Lille, France.
    Corchado, Juan Manuel
    University of Salamanca, Salamanca, Spain; AIR Institute, Salamanca, Spain.
    De La Prieta, Fernando
    University of Salamanca, Salamanca, Spain.
    Preface2022In: Advances in practical applications of agents, multi-agent systems, and complex systems simulation: the PAAMS collection : 20th International Conference, PAAMS 2022, L’Aquila, Italy, July 13–15, 2022, Proceedings / [ed] Frank Dignum; Philippe Mathieu; Juan Manuel Corchado; Fernando De La Prieta, Springer, 2022, p. vi-Chapter in book (Other academic)
  • 17.
    Dignum, Virginia
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Agents are dead. Long live agents!2020In: AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems, Association for Computing Machinery (ACM), 2020, p. 1701-1705Conference paper (Refereed)
    Abstract [en]

    In recent years, the future of agent research has often been discussed. Most prominent is the issue whether agents should be seen as a conceptual framework or as a software development paradigm. At the same time, developments on AI seem to have taken the field into a new direction. In this paper we argue that in order for agents research to create added value for actual, real problems in the world we need to reconsider possible agent architectures and their strengths and weaknesses, their overlaps and commonalities. Finally we present a first sketch of an architecture for such agents.

  • 18.
    Erdogan, Emre
    et al.
    Utrecht University, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Verbrugge, Rineke
    University of Groningen, Groningen, Netherlands.
    Yolum, Plnar
    Utrecht University, Utrecht, Netherlands.
    Abstracting minds: computational theory of mind for human-agent collaboration2022In: HHAI2022: augmenting human intellect: Proceedings of the first international conferenceon hybrid human-artificial intelligence / [ed] Stefan Schlobach; María Pérez-Ortiz; Myrthe Tielman, IOS Press, 2022, Vol. 354, p. 199-211Conference paper (Refereed)
    Abstract [en]

    Theory of mind refers to the human ability to reason about mental content of other people such as beliefs, desires, and goals. In everyday life, people rely on their theory of mind to understand, explain, and predict the behaviour of others. Having a theory of mind is especially useful when people collaborate, since individuals can then reason on what the other individual knows as well as what reasoning they might do. Realization of hybrid intelligence, where an agent collaborates with a human, will require the agent to be able to do similar reasoning through computational theory of mind. Accordingly, this paper provides a mechanism for computational theory of mind based on abstractions of single beliefs into higher-level concepts. These concepts can correspond to social norms, roles, as well as values. Their use in decision making serves as a heuristic to choose among interactions, thus facilitating collaboration on decisions. Using examples from the medical domain, we demonstrate how having such a theory of mind enables an agent to interact with humans efficiently and can increase the quality of the decisions humans make.

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  • 19.
    Erdogan, Emre
    et al.
    Utrecht University, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands.
    Verbrugge, Rineke
    University of Groningen, Groningen, Netherlands.
    Yolum, Pınar
    Utrecht University, Utrecht, Netherlands.
    Computational theory of mind for human-agent coordination2022In: Coordination, organizations, institutions, norms, and ethics for governance of multi-agent systems XV: International workshop, COINE 2022, virtual event, May 9, 2022, revised selected papers / [ed] Nirav Ajmeri; Andreasa Morris Martin, Bastin Tony Roy Savarimuthu, Springer Nature, 2022, p. 92-108Conference paper (Refereed)
    Abstract [en]

    In everyday life, people often depend on their theory of mind, i.e., their ability to reason about unobservable mental content of others to understand, explain, and predict their behaviour. Many agent-based models have been designed to develop computational theory of mind and analyze its effectiveness in various tasks and settings. However, most existing models are not generic (e.g., only applied in a given setting), not feasible (e.g., require too much information to be processed), or not human-inspired (e.g., do not capture the behavioral heuristics of humans). This hinders their applicability in many settings. Accordingly, we propose a new computational theory of mind, which captures the human decision heuristics of reasoning by abstracting individual beliefs about others. We specifically study computational affinity and show how it can be used in tandem with theory of mind reasoning when designing agent models for human-agent negotiation. We perform two-agent simulations to analyze the role of affinity in getting to agreements when there is a bound on the time to be spent for negotiating. Our results suggest that modeling affinity can ease the negotiation process by decreasing the number of rounds needed for an agreement as well as yield a higher benefit for agents with theory of mind reasoning.

  • 20. Ferrando, Angelo
    et al.
    Winikoff, Michael
    Cranefield, Stephen
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Mascardi, Viviana
    On Enactability of Agent Interaction Protocols: Towards a Unified Approach2019In: AAMAS '19: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, ACM Digital Library, 2019, p. 1955-1957Conference paper (Refereed)
    Abstract [en]

    Interactions between agents are usually designed from a global viewpoint. However, the implementation of a multi-agent interaction is distributed. This difference can introduce problems. For instance, it is possible to specify protocols from a global viewpoint that cannot be implemented as a collection of individual agents. This leads naturally to the question of whether a given (global) protocol is enactable. We consider this question in a powerful setting (trace expressions), considering a range of message ordering interpretations (specifying what it means to say that an interaction step occurs before another), and a range of possible constraints on the semantics of message delivery, corresponding to different properties of the underlying communication middleware.

  • 21.
    Gentile, Manuel
    et al.
    Institute for Educational Technology, National Research Council of Italy, Palermo, Italy.
    Città, Giuseppe
    Institute for Educational Technology, National Research Council of Italy, Palermo, Italy.
    Marfisi-Schottman, Iza
    EA4023 Laboratoire d'Informatique de l'Université du Mans (LIUM), Le Mans, France.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Allegra, Mario
    Institute for Educational Technology, National Research Council of Italy, Palermo, Italy.
    Editorial: Artificial intelligence for education2023In: Frontiers in Education, E-ISSN 2504-284X, Vol. 8, article id 1276546Article in journal (Other academic)
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  • 22.
    Gholizadeh Ansari, Saba
    et al.
    Utrecht University, Utrecht, Netherlands.
    Prasetya, I.S.W.B.
    Utrecht University, Utrecht, Netherlands.
    Dastani, Mehdi
    Utrecht University, Utrecht, Netherlands.
    Keller, Gabriele
    Utrecht University, Utrecht, Netherlands.
    Prandi, Davide
    Fondazione Bruno Kessler, Trento, Italy.
    Kifetew, Fitsum Meshesha
    Fondazione Bruno Kessler, Trento, Italy.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    PX-MBT: A framework for model-based player experience testing2024In: Science of Computer Programming, ISSN 0167-6423, E-ISSN 1872-7964, Vol. 236, article id 103108Article in journal (Refereed)
    Abstract [en]

    As video games become more complex and widespread, player experience (PX) testing becomes crucial in the game industry. Attracting and retaining players are key elements to guarantee the success of a game in the highly competitive market. Although a number of techniques have been introduced to measure the emotional aspect of the experience, automated testing of player experience still needs to be explored. This paper presents PX-MBT, a framework for automated player experience testing with emotion pattern verification. PX-MBT (1) utilizes a model-based testing approach for test suite generation, (2) employs a computational model of emotions developed based on a psychological theory of emotions to model players' emotions during game-plays with an intelligent agent, and (3) verifies emotion patterns given by game designers on executed test suites to identify PX-issues. We explain PX-MBT architecture and provide an example along with its result in emotion pattern verification, which asserts the evolution of emotions over time, and heat-maps to showcase the spatial distribution of emotions on the game map.

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  • 23.
    Heidari, Samaneh
    et al.
    Utrecht University, Utrecht, Netherlands.
    Wijermans, Nanda
    Stockholm University, Stockholm, Sweden.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands.
    Agents with dynamic social norms2020In: Multi-agent-based simulation XX: 20th International Workshop, MABS 2019, Montreal, QC, Canada, May 13, 2019, revised selected papers / [ed] Mario Paolucci; Jaime Simão Sichman; Harko Verhagen, Springer, 2020, p. 112-124Conference paper (Refereed)
    Abstract [en]

    Social norms are important as societal agreements of acceptable behavior. They can be seen as flexible, but stable constraints on individual behavior. However, social norms themselves are not completely static. Norms emerge from dynamic environments and changing agent populations. They adapt and in the end also get abrogated. Although norm emergence has received attention in the literature, its focus is mainly describing the rise of new norms based on individual preferences and punishments on violations. This explanation works for environments where personal preferences are stable and known. In this paper, we argue that values are the stable concepts that allow for explaining norm change in situations where agents can move between social groups in a dynamic environment (as is the case in most realistic social simulations for policy support). Values thus reflect the stable concept that those are shared between the agents of a group and can direct norm emergence, adaptation, and abrogation. We present the norm framework that enables describing and modeling value and situation based norm change and demonstrate its potential application using a simple example.

  • 24.
    Jensen, Maarten
    et al.
    Utrecht University, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands; CVUT Prague, Prague, Czech Republic.
    Drug Trafficking As Illegal Supply Chain - A Social Simulation2021In: Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23–27 September 2019 / [ed] Petra Ahrweiler, Martin Neumann, Springer, 2021, p. 9-22Conference paper (Refereed)
    Abstract [en]

    Cocaine trafficking is starting to get modeled by supply chain theory. Supply chain theories are described in many economical papers. These theories are however not directly usable in analyzing illegal supply chains. In this paper we investigate the difference between legal and illegal supply chains. Where the difference of the supply chain lies in two factors, these are trust and risk. Here we model a cocaine trafficking supply chain based on legal supply chain theory. This model will be copied and adjusted with theoretical concepts that are inherent to an illegal supply chain. Comparison of the results of the two models showed that differences in those factors lead to differences in the supply chain, such as clustering and efficiency.

  • 25.
    Jensen, Maarten
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Vanhée, Loïs
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dynamic context-sensitive deliberation2024In: Multi-Agent-Based simulation XXIV: 24th International workshop, MABS 2023 London, UK, May 29 – June 2, 2023 Revised selected papers / [ed] Luis G. Nardin; Sara Mehryar, Springer Nature, 2024, p. 112-126Chapter in book (Refereed)
    Abstract [en]

    Truly realistic models for policy making require multiple aspects of life, realistic social behaviour and the ability to simulate millions of agents. Current state of the art Agent-based models only achieve two of these requirements. Models that prioritise realistic social behaviour are not easily scalable because the complex deliberation takes into account all information available at each time step for each agent. Our framework uses context to considerably narrow down the information that has to be considered. A key property of the framework is that it can dynamically slide between fast deliberation and complex deliberation. Context is expanded based on necessity. We introduce the elements of the framework, describe the architecture and show a proof-of-concept implementation. We give first steps towards validation using this implementation.

  • 26.
    Jensen, Maarten
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Verhagen, Harko
    Department of Computer and Systems Sciences, Stockholm University, PO Box 7003, Kista, Sweden.
    Vanhée, Loïs
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Towards Efficient Context-Sensitive Deliberation2022In: Advances in Social Simulation: Proceedings of the 16th Social Simulation Conference, 20–24 September 2021 / [ed] Marcin Czupryna; Bogumił Kamiński, Springer Science+Business Media B.V., 2022, p. 409-421Conference paper (Refereed)
    Abstract [en]

    We propose a context-sensitive deliberation framework where the decision context does not deliver an action straight away, but where rather the decision context and agent characteristics influence the type of deliberation and type of information evaluated which will affect the final decision. The framework is based on the Contextual Action Framework for Computational Agents (CAFCA). Our framework also tailors the deliberation type used to the decision context the agent finds itself in, starting from the least cognitive taxing deliberation types unless the context requires more complex deliberation types. As a proof-of-concept the paper shows how context and information relevance can be used to conceptually expand the deliberation system of an agent.

  • 27.
    Kammler, Christian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Wijermans, Nanda
    Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
    Utilizing the full potential of norms for the agent’s decision process2023In: Advances in social simulation: Proceedings of the 17th Social Simulation Conference, European Social Simulation Association, Cham: Springer, 2023, p. 193-205Conference paper (Refereed)
    Abstract [en]

    Norms are a crucial part of human behavior that received a lot of attention within the social simulation community. However, some aspects—up until now—have not been addressed in existing agent architectures, such as their motivational aspects and their importance and impact in planning and action selection. In this paper we present an agent architecture capable of grasping this potential of norms. We use perspectives to reflect how different people engage with a norm, and how it effects their long-term goals, their planning, and course of action. Our architecture is capable of having fast habitual-like behavior, as well as more complex deliberation if necessary.

  • 28.
    Kammler, Christian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Wijermans, Nanda
    Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden.
    Lindgren, Helena
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Changing Perspectives: Adaptable Interpretations of Norms for Agents2022In: Multi-Agent-Based Simulation XXII: 22nd International Workshop, MABS 2021, Virtual Event, May 3-7, 2021, Revised Selected Papers / [ed] Koen H. Van Dam; Nicolas Verstaevel, Springer, 2022, Vol. 13128 LNAI, p. 139-152Conference paper (Refereed)
    Abstract [en]

    For agent-based social simulations to be a powerful tool for policy makers and other decision makers in a given context (e.g. the current COVID-19 pandemic), they need to be socially realistic and thus, appropriately represent complex social concepts, such as social rules. In this paper, we focus on norms. Norms describe ‘normal’ behavior and aim at assuring the interests and values of groups or the society as a whole. People react differently to norms, and focus only on the parts that are relevant for them. Furthermore, norms are not only restrictions on behavior, but also trigger new behavior. Seeing a norm only as a restriction on certain behavior misses important aspects and leads to simulations that can be very misleading. Different perspectives need to be incorporated into the simulation to capture the variety of ways different stakeholders react to a norm and how this affects their interaction. We therefore present an approach to include these different perspectives on norms, and their consequences for different people and groups in decision support simulations. A perspective is specified by their goals, actions, effects of those actions, priorities in values, and social affordances. Through modeling perspectives we enable policy makers and other decision makers (the users) to be active in the modeling process and to tailor the simulation to their specific needs, by representing norms as modifiable objects, and providing textual and graphical representations of norms. This provides them with differentiated insights meaningful for the decisions they are faced with. We indicate the requirements for both the simulation platform as well as the agents that follow from our approach. Early explorations of our social simulation are showing the necessity of our approach.

  • 29.
    Kammler, Christian
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Mellema, Rene
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Agents dealing with norms and regulations2023In: Multi-agent-based simulation XXIII: 23rd International Workshop, MABS 2022, virtual event, May 8-9, 2022: Revised selected papers / [ed] Fabian Lorig; Emma Norling, Springer Science+Business Media B.V., 2023, p. 134-146Conference paper (Refereed)
    Abstract [en]

    Norms influence behaviour in many ways. In situations such as the COVID-19 pandemic where the effect of policies on the spread of the virus is evaluated, this leads to disputes about their effectiveness. In order to build agent-based social simulations that give proper support for this evaluation process we need agents that properly deal with norms. In this paper we present a new agent deliberation architecture that takes more aspects of norms into account than traditional architectures have done. Dealing properly with norms means that agents can reason through the consequences of the norms, that they are used to motivate and not just constrain behaviour, and that the agents can violate the norm as well. For the former we use the ideas of perspectives on norms, while the latter is enabled through the use of values. Within our architecture we can also represent habitual behaviour, context sensitive planning, and through the use of landmarks, reactive planning. We use the example of a restaurant-size based restriction to show how our architecture works.

  • 30.
    Kreulen, Kurt
    et al.
    Faculty of technology, policy and management, Technical University (TU) of Delft, Jaffalaan 5, Delft, Netherlands.
    de Bruin, Bart
    Faculty of technology, policy and management, Technical University (TU) of Delft, Jaffalaan 5, Delft, Netherlands.
    Ghorbani, Amineh
    Faculty of technology, policy and management, Technical University (TU) of Delft, Jaffalaan 5, Delft, Netherlands.
    Mellema, René
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kammler, Christian
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Vanhee, Loïs
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    How culture influences individual behavior during a pandemic: a social simulation of the COVID-19 crisis2022In: JASSS: Journal of Artificial Societies and Social Simulation, E-ISSN 1460-7425, Vol. 25, no 3, article id 6Article in journal (Refereed)
    Abstract [en]

    Since its first appearance in Wuhan (China), countries have been employing, to varying degrees of success, a series of non-pharmaceutical interventions aimed at limiting the spread of SARS-CoV-2 within their populations. In this article, we build on scientific work that demonstrates that culture is part of the explanation for the observed variability between countries in their ability to effectively control the transmission of SARS-CoV-2. We present a theoretical framework of how culture influences decision-making at the level of the individual. This conceptualization is formalized in an agent-based model that simulates how cultural factors can combine to produce differences across populations in terms of the behavioral responses of individuals to the COVID-19 crisis. We illustrate that, within our simulated environment, the culturally-dependent willingness of people to comply with public health related measures might constitute an important determinant of differences in infection dynamics across populations. Our model generates the highest rates of non-compliance within cultures marked as individualist, progressive and egalitarian. Our model illustrates the potential role of culture as a population-level predictor of infections associated with COVID-19. In doing so, the model, and theoretical framework on which it is based, may inform future studies aimed at incorporating the effect of culture on individual decision-making processes during a pandemic within social simulation models.

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  • 31.
    Lobo, Inês
    et al.
    INESC-ID and Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal.
    Rato, Diogo
    INESC-ID and Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal.
    Prada, Rui
    INESC-ID and Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Socially Aware Interactions: From Dialogue Trees to Natural Language Dialogue Systems2022In: Chatbot Research and Design / [ed] Asbjørn Følstad; Theo Araujo; Symeon Papadopoulos; Effie L.-C. Law; Ewa Luger, Springer Science+Business Media B.V., 2022, p. 124-140Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a prototype of a human-agent dialogue system, in which the scenarios are easy-to-author, as in tree-based dialogue tools. These, however, only allow for scripted and restricted dialogues. For this reason, we focused on developing a flexible and robust deliberation mechanism as well, based on the Cognitive Social Frames model and the theory of social practices, so that the conversational agent could provide acceptable responses according to different social contexts. Having access to sequences of frames containing small dialogue trees, the agent activates the most salient frame to reply appropriately to the user’s input. As a proof of concept, we designed a medical diagnosis scenario between a doctor and a patient in which the agent could play both roles given different settings of the scenario. In this prototype, the user had to choose from a limited set of alternatives, based on the current context, in order to respond to the agent; however, in the future, we intend to allow users to write freely, expecting to be able to map their utterances to the appropriate context.

  • 32.
    Lorig, Fabian
    et al.
    Department of Computer Science and Media Technology, Internet of Things and People Research Center, Malmö University, Malmö, Sweden.
    Vanhée, Loïs
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Agent-based social simulation for policy making2023In: Human-centered artificial intelligence: Advanced lectures, Springer Nature, 2023, p. 391-414Conference paper (Refereed)
    Abstract [en]

    In agent-based social simulations (ABSS), an artificial population of intelligent agents that imitate human behavior is used to investigate complex phenomena within social systems. This is particularly useful for decision makers, where ABSS can provide a sandpit for investigating the effects of policies prior to their implementation. During the Covid-19 pandemic, for instance, sophisticated models of human behavior enable the investigation of the effects different interventions can have and even allow for analyzing why a certain situation occurred or why a specific behavior can be observed. In contrast to other applications of simulation, the use for policy making significantly alters the process of model building and assessment, and requires the modelers to follow different paradigms. In this chapter, we report on a tutorial that was organized as part of the ACAI 2021 summer school on AI in Berlin, with the goal of introducing agent-based social simulation as a method for facilitating policy making. The tutorial pursued six Intended Learning Outcomes (ILOs), which are accomplished by three sessions, each of which consists of both a conceptual and a practical part. We observed that the PhD students participating in this tutorial came from a variety of different disciplines, where ABSS is mostly applied as a research method. Thus, they do often not have the possibility to discuss their approaches with ABSS experts. Tutorials like this one provide them with a valuable platform to discuss their approaches, to get feedback on their models and architectures, and to get impulses for further research.

  • 33.
    Mathieu, Philippe
    et al.
    University of Lille, Lille, France.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Novais, Paulo
    Universidade do Minho, Braga, Portugal.
    De la Prieta, Fernando
    University of Salamanca, Salamanca, Spain.
    Preface2023In: Advances in practical applications of agents, multi-agent systems, and cognitive mimetics. The PAAMS collection: 21st International conference, PAAMS 2023, Guimarães, Portugal, July 12–14, 2023, proceedings / [ed] Philippe Mathieu; Frank Dignum; Paulo Novais; Fernando De la Prieta, Springer Nature, 2023Chapter in book (Other academic)
  • 34.
    Melchior, A.
    et al.
    Department of Information and Computer Science, Utrecht University, Utrecht, Netherlands; Ministry of Economic Affairs and Climate Policy and Ministry of Agriculture, Nature and Food Quality, Utrecht, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Department of Information and Computer Science, Utrecht University, Utrecht, Netherlands; Department of Computer Science, Czech University of Technology in Prague, Prague, Czech Republic.
    Ruiz, M.
    School of Engineering, Zurich University of Applied Sciences, Zurich, Switzerland.
    A Closer Look at Dutch Policy Development2021In: Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23–27 September 2019, Springer, 2021, p. 383-395Conference paper (Refereed)
    Abstract [en]

    In the world of Agent-Based Modelling we claim that models and simulations are well suited to aid policy development. Yet it proves difficult to find the right connection with policy developers. In this paper we provide various insights in the policy development world in the context of the Dutch national government. We discuss relevant literature, report on conducted interviews with policy developers and reflect on participatory observations while working in Dutch ministries. This provides us with a set of needs and goals of (Dutch) policy developers. It also thought us that the policy process and the policy developer do not exist. A policy is only one element in the policy process. We found different elements in the policy process for which ABM’s can be used, like consensus building or communication of problem understanding. We pose that ABM is currently not fit to predict policy outcomes in our context. After discussing these elements we have summarized them in requirements that can be operationalized by us and others to find a better connection with policy developers. The requirements are a starting point for a framework that supports policy developers in their work with ABM.

  • 35.
    Mellema, Rene
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jensen, Maarten
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Social rules for agent systems2021In: Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII: International Workshops COIN 2017 and COINE 2020, Sao Paulo, Brazil, May 8-9, 2017 and Virtual Event, May 9, 2020, Revised Selected Papers / [ed] Aler Tubella A., Cranefield S., Frantz C., Meneguzzi F., Vasconcelos W., 2021, p. 175-180Conference paper (Refereed)
    Abstract [en]

    When creating (open) agent systems it has become common practice to use social concepts such as social practices, norms and conventions to model the way the interactions between the agents are regulated. However, in the literature most papers concentrate on only one of these aspects at the time. Therefore there is hardly any research on how these social concepts relate. It is also unclear whether something like a norm evolves from a social practice or convention or whether they are complete independent entities. In this paper we investigate some of the conceptual differences between these concepts. Whether they are fundamentally stemming from a single social object or should be seen as different types of objects altogether. And finally, when one should which type of concept in an implementation or a combination of them.

  • 36.
    Mertens, A.
    et al.
    Ghent University, Ghent, Belgium.
    Feliciani, Thomas
    University College Dublin, Dublin, Ireland.
    Heidari, S.
    Utrecht University, Utrecht, Netherlands.
    Siebers, Peer-Olaf
    University of Nottingham, Nottingham, United Kingdom.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands.
    Are We Done Yet? or When is Our Model Perfect (Enough)?2021In: Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23–27 September 2019, Springer, 2021, p. 285-290Conference paper (Refereed)
  • 37. Nanni, Mirco
    et al.
    Andrienko, Gennady
    Barabasi, Albert-Laszlo
    Boldrini, Chiara
    Bonchi, Francesco
    Cattuto, Ciro
    Chiaromonte, Francesca
    Comande, Giovanni
    Conti, Marco
    Cote, Mark
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Domingo-Ferrer, Josep
    Ferragina, Paolo
    Giannotti, Fosca
    Guidotti, Riccardo
    Helbing, Dirk
    Kaski, Kimmo
    Kertesz, Janos
    Lehmann, Sune
    Lepri, Bruno
    Lukowicz, Paul
    Matwin, Stan
    Jimenez, David Megias
    Monreale, Anna
    Morik, Katharina
    Oliver, Nuria
    Passarella, Andrea
    Passerini, Andrea
    Pedreschi, Dino
    Pentland, Alex
    Pianesi, Fabio
    Pratesi, Francesca
    Rinzivillo, Salvatore
    Ruggieri, Salvatore
    Siebes, Arno
    Torra, Vicenc
    Trasarti, Roberto
    van den Hoven, Jeroen
    Vespignani, Alessandro
    Give more data, awareness and control to individual citizens, and they will help COVID-19 containment2020In: Transactions on Data Privacy, ISSN 1888-5063, E-ISSN 2013-1631, Vol. 13, no 1, p. 61-66Article in journal (Refereed)
    Abstract [en]

    The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores", to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allowthe user to share spatio-temporal aggregates - if and when they want and for specific aims - with health authorities, for instance. Second, we favour a longerterm pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.

  • 38. Nanni, Mirco
    et al.
    Andrienko, Gennady
    Barabasi, Albert-Laszlo
    Boldrini, Chiara
    Bonchi, Francesco
    Cattuto, Ciro
    Chiaromonte, Francesca
    Comande, Giovanni
    Conti, Marco
    Cote, Mark
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Domingo-Ferrer, Josep
    Ferragina, Paolo
    Giannotti, Fosca
    Guidotti, Riccardo
    Helbing, Dirk
    Kaski, Kimmo
    Kertesz, Janos
    Lehmann, Sune
    Lepri, Bruno
    Lukowicz, Paul
    Matwin, Stan
    Jimenez, David Megias
    Monreale, Anna
    Morik, Katharina
    Oliver, Nuria
    Passarella, Andrea
    Passerini, Andrea
    Pedreschi, Dino
    Pentland, Alex
    Pianesi, Fabio
    Pratesi, Francesca
    Rinzivillo, Salvatore
    Ruggieri, Salvatore
    Siebes, Arno
    Torra, Vicenç
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Maynooth University, Maynooth, Ireland.
    Trasarti, Roberto
    Hoven, Jeroen van den
    Vespignani, Alessandro
    Give more data, awareness and control to individual citizens, and they will help COVID-19 containment2021In: Ethics and Information Technology, ISSN 1388-1957, E-ISSN 1572-8439, Vol. 23, p. 1-6Article in journal (Refereed)
    Abstract [en]

    The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates—if and when they want and for specific aims—with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.

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  • 39.
    Pedreschi, Dino
    et al.
    University of Pisa, Pisa, Italy.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Morini, Virginia
    University of Pisa, Pisa, Italy; KDD Lab ISTI-CNR, Pisa, Italy.
    Pansanella, Valentina
    Scuola Normale Superiore, Pisa, Italy; KDD Lab ISTI-CNR, Pisa, Italy.
    Cornacchia, Giuliano
    University of Pisa, Pisa, Italy; KDD Lab ISTI-CNR, Pisa, Italy.
    Towards a Social Artificial Intelligence2023In: Human-Centered Artificial Intelligence: Advanced Lectures / [ed] Mohamed Chetouani; Virginia Dignum; Paul Lukowicz; Carles Sierra, Springer, 2023, p. 415-428Conference paper (Refereed)
    Abstract [en]

    Artificial Intelligence can both empower individuals to face complex societal challenges and exacerbate problems and vulnerabilities, such as bias, inequalities, and polarization. For scientists, an open challenge is how to shape and regulate human-centered Artificial Intelligence ecosystems that help mitigate harms and foster beneficial outcomes oriented at the social good. In this tutorial, we discuss such an issue from two sides. First, we explore the network effects of Artificial Intelligence and their impact on society by investigating its role in social media, mobility, and economic scenarios. We further provide different strategies that can be used to model, characterize and mitigate the network effects of particular Artificial Intelligence driven individual behavior. Secondly, we promote the use of behavioral models as an addition to the data-based approach to get a further grip on emerging phenomena in society that depend on physical events for which no data are readily available. An example of this is tracking extremist behavior in order to prevent violent events. In the end, we illustrate some case studies in-depth and provide the appropriate tools to get familiar with these concepts.

  • 40. Prada, Rui
    et al.
    Prasetya, I. S. W. B.
    Kifetew, Fitsum
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Vos, Tanja E. J.
    Lander, Jason
    Donnart, Jean-yves
    Kazmierowski, Alexandre
    Davidson, Joseph
    Fernandes, Pedro M.
    Agent-based Testing of Extended Reality Systems2020In: 2020 IEEE 13TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VALIDATION AND VERIFICATION (ICST 2020), IEEE Communications Society, 2020, p. 414-417Conference paper (Refereed)
    Abstract [en]

    Testing for quality assurance (QA) is a crucial step in the development of Extended Reality (XR) systems that typically follow iterative design and development cycles. Bringing automation to these testing procedures will increase the productivity of XR developers. However, given the complexity of the XR environments and the User Experience (UX) demands, achieving this is highly challenging. We propose to address this issue through the creation of autonomous cognitive test agents that will have the ability to cope with the complexity of the interaction space by intelligently explore the most prominent interactions given a test goal and support the assessment of affective properties of the UX by playing the role of users.

  • 41.
    Prasetya, I. S. W. B.
    et al.
    Utrecht University, Utrecht, The Netherlands.
    Prada, Rui
    Inst. de Eng. de Sistemas e Computadores - Investiga¸c˜ao e Desenv, Lisbon, Portugal.
    Vos, Tanja E. J.
    Univ. Politecnica de Valencia, Valencia, Spain; Open University, Heerlen, The Netherlands.
    Kifetew, Fitsum
    Fondazione Bruno Kessler, Trento, Italy.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Lander, Jason
    Gameware, Newmarket, UK.
    Donnart, Jean-Yves
    Thales AVS, Paris, France.
    Kazmierowski, Alexandre
    Thales SIX GTS, Paris, France.
    Davidson, Joseph
    GoodAI, Prague, Czech Republic.
    Ricos, Fernando Pastor
    Univ. Politecnica de Valencia, Valencia, Spain; Open University, Heerlen, The Netherlands.
    IV4XR-intelligent verification/validation for extended reality based systems2020In: Research challenges in information science: 14th international conference, RCIS 2020, Limassol, Cyprus, September 23–25, 2020, proceedings / [ed] Fabiano Dalpiaz; Jelena Zdravkovic; Pericles Loucopoulos, Cham: Springer, 2020, Vol. 385, p. 647-649Conference paper (Refereed)
  • 42.
    Prasetya, I.S.W.B.
    et al.
    Utrecht University, Utrecht, Netherlands.
    Dastani, Mehdi
    Utrecht University, Utrecht, Netherlands.
    Prada, Rui
    Inst. de Engenharia de Sistemas e Computadores - Investigação e Desenvolvimento, Lisbon, Portugal.
    Vos, Tanja E. J.
    Universidad Politecnica de Valencia, Valencia, Spain; Open University, Heerlen, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kifetew, Fitsum
    Fondazione Bruno Kessler, Trento, Italy.
    Aplib: Tactical Agents for Testing Computer Games2020In: Engineering Multi-Agent Systems: 8th International Workshop, EMAS 2020, Auckland, New Zealand, May 8–9, 2020, Revised Selected Papers / [ed] Cristina Baroglio, Jomi F. Hubner, Michael Winikoff, Springer, 2020, p. 21-41Conference paper (Refereed)
    Abstract [en]

    Modern interactive software, such as computer games, employ complex user interfaces. Although these user interfaces make the games attractive and powerful, unfortunately they also make them extremely difficult to test. Not only do we have to deal with their functional complexity, but also the fine grained interactivity of their user interface blows up their interaction space, so that traditional automated testing techniques have trouble handling it. An agent-based testing approach offers an alternative solution: agents’ goal driven planning, adaptivity, and reasoning ability can provide an extra edge towards effective navigation in complex interaction space. This paper presents aplib, a Java library for programming intelligent test agents, featuring novel tactical programming as an abstract way to exert control over agents’ underlying reasoning-based behavior. This type of control is suitable for programming testing tasks. Aplib is implemented in such a way to provide the fluency of a Domain Specific Language (DSL). Its embedded DSL approach also means that aplib programmers will get al.l the advantages that Java programmers get: rich language features and a whole array of development tools.

  • 43.
    Savarimuthu, Bastin Tony Roy
    et al.
    Department of Information Science, University of Otago, Dunedin, New Zealand.
    Licorish, Sherlock A.
    Department of Information Science, University of Otago, Dunedin, New Zealand.
    Devananda, Manjula
    Department of Information Science, University of Otago, Dunedin, New Zealand.
    Greenheld, Georgia
    Department of Information Science, University of Otago, Dunedin, New Zealand.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Developers’ Responses to App Review Feedback – A Study of Communication Norms in App Development2021In: Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII: International Workshops COIN 2017 and COINE 2020, Sao Paulo, Brazil, May 8-9, 2017 and Virtual Event, May 9, 2020, Revised Selected Papers / [ed] Andrea Aler Tubella, Stephen Cranefield, Christopher Frantz, Felipe Meneguzzi, Wamberto Vasconcelos, Springer Nature, 2021, p. 57-75Conference paper (Refereed)
    Abstract [en]

    Norms are general expectations of behavior in societies. Huge amount of computer-mediated interaction data available in the social media domain provides an opportunity to extract and study communication norms, both to understand their prevalence and to make informed decisions about adopting them. While interactions in social media platforms such as Twitter and Facebook have been widely studied, only recently researchers have started examining app reviews provided by users and the responses provided by developers in the domain of app development. In this vein, a lot of attention has been devoted to study the nature of user reviews, however, little is known about developer responses to such reviews. Additionally, no other prior work has scrutinized the nature of communication norms in this domain. Towards addressing these gaps, this work pursues three objectives using a dataset comprising user reviews and developer responses from Google’s top-20 apps used to track running with a total of 24,407 reviews and 2,668 responses. First, based on prior literature in computer-mediated interactions, the study identifies 12 norms in responses provided by developers in three categories (obligation norms, prohibition norms and domain-specific response norms). Second, it scrutinizes the awareness and adoption of these norms. Third, based on the results obtained, this study identifies the need for creating a response recommendation system that generates responses to user reviews either automatically, or with some help from the developers. The proposed response recommendation system is a normative system that will generate responses that abide by the norms identified in this work, and will also monitor potential norm violations (if the responses were to be modified by the developers). Development of such a system forms the focus of future work.

  • 44.
    Shirzadehhajimahmood, Samira
    et al.
    Utrecht University, Netherlands.
    Prasetya, I.S.W.B.
    Utrecht University, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dastani, Mehdi
    Utrecht University, Netherlands.
    An online agent-based search approach in automated computer game testing with model construction2022In: A-TEST 2022: Proceedings of the 13th International Workshop on Automating Test Case Design, Selection and Evaluation, ACM Digital Library, 2022, p. 45-52Conference paper (Refereed)
    Abstract [en]

    The complexity of computer games is ever increasing. In this setup, guiding an automated test algorithm to find a solution to solve a testing task in a game's huge interaction space is very challenging. Having a model of a system to automatically generate test cases would have a strong impact on the effectiveness and efficiency of the algorithm. However, manually constructing a model turns out to be expensive and time-consuming. In this study, we propose an online agent-based search approach to solve common testing tasks when testing computer games that also constructs a model of the system on-the-fly based on the given task, which is then exploited to solve the task. To demonstrate the efficiency of our approach, a case study is conducted using a game called Lab Recruits.

  • 45.
    Shirzadehhajimahmood, Samira
    et al.
    Utrecht University, Netherlands.
    Prasetya, I.S.W.B.
    Utrecht University, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dastani, Mehdi
    Utrecht University, Netherlands.
    Keller, Gabriele
    Utrecht University, Netherlands.
    Using an agent-based approach for robust automated testing of computer games2021In: A-TEST 2021 - Proceedings of the 12th International Workshop on Automating TEST Case Design, Selection, and Evaluation, co-located with ESEC/FSE 2021 / [ed] Yaman S.G., Yaman S.G., Prada R., Kifetew R.M., Cardozo N., Association for Computing Machinery (ACM), 2021, p. 1-8Conference paper (Refereed)
    Abstract [en]

    Modern computer games typically have a huge interaction spaces and non-deterministic environments. Automation in testing can provide a vital boost in development and it further improves the overall software's reliability and efficiency. Moreover, layout and game logic may regularly change during development or consecutive releases which makes it difficult to test because the usage of the system continuously changes. To deal with the latter, tests also need to be robust. Unfortunately, existing game testing approaches are not capable of maintaining test robustness. To address these challenges, this paper presents an agent-based approach for robust automated testing based on the reasoning type of AI.

  • 46.
    Smith, Wally
    et al.
    The University of Melbourne, Melbourne, Australia.
    Kirley, Michael
    The University of Melbourne, Melbourne, Australia.
    Sonenberg, Liz
    The University of Melbourne, Melbourne, Australia.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    The Role of Environments in Affording Deceptive Behaviour: Some Preliminary Insights from Stage Magic2021In: Deceptive AI: First International Workshop, DeceptECAI 2020, Santiago de Compostela, Spain, August 30, 2020 and Second International Workshop, DeceptAI 2021, Montreal, Canada, August 19, 2021, Proceedings, Springer Nature, 2021, p. 17-26Conference paper (Refereed)
    Abstract [en]

    Drawing on an ecological perspective, we contend that research into deception in AI needs to consider not only the cognitive structures of would-be deceptive agents but also the nature of the environments in which they act. To illustrate this approach, we report work-in-progress to design a game called MindTrails, played between a software agent and a human opponent, that is informed by the principles of stage magic to embed deceptive possibilities into its game world. MindTrails is intended to have well-defined elements and rules, while being complex enough to afford a rich range of deceptive behaviours. In this way, it allows us to more precisely articulate some of the deceptive principles of the stage magician and render them more accessible to AI methods and researchers.

  • 47.
    van den Hurk, Mijke
    et al.
    Utrecht University, Utrecht, Netherlands; Dutch National Police, Dutch, Netherlands.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands; CVUT Prague, Prague, Czech Republic.
    Towards Fundamental Models of Radicalization2021In: Advances in Social Simulation: Proceedings of the 15th Social Simulation Conference: 23–27 September 2019, Springer, 2021, p. 67-79Conference paper (Refereed)
    Abstract [en]

    This paper proposes a multi-agent based model of radicalization, based on the theoretical framework from [1]. The model combines the need for significance with ideology and social group theory, in order to create radical behavior. With this model a first attempt is made for a fundamental model that can be used to get better insights in the mechanism behind radicalization. Results show that agents do radicalize and that this leads to the formation of isolated social groups. Furthermore, results show that radicalization does not just depend on a deviating mental attitude, but is a combination of individual and context characteristics.

  • 48.
    van Zoelen, Emma M.
    et al.
    TNO, Soesterberg, Netherlands.
    Cremers, Anita
    TNO, Soesterberg, Netherlands; University of Applied Sciences, Utrecht, Netherlands.
    Dignum, Frank P. M.
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Utrecht University, Utrecht, Netherlands; Czech Technical University, Czech Republic.
    van Diggelen, Jurriaan
    TNO, Soesterberg, Netherlands.
    Peeters, Marieke M.
    TNO, Soesterberg, Netherlands.
    Learning to communicate proactively in human-agent teaming2020In: Highlights in practical applications of agents, multi-agent systems, and trust-worthiness. The PAAMS Collection: international workshops of PAAMS 2020, L'Aquila, Italy, October 7–9, 2020, proceedings / [ed] Fernando De La Prieta; Philippe Mathieu; Jaime Andrés Rincón Arango; Alia El Bolock; Elena Del Val; Jaume Jordán Prunera; João Carneiro; Rubén Fuentes; Fernando Lopes; Vicente Julian, Springer, 2020, p. 238-249Conference paper (Refereed)
    Abstract [en]

    Artificially intelligent agents increasingly collaborate with humans in human-agent teams. Timely proactive sharing of relevant information within the team contributes to the overall team performance. This paper presents a machine learning approach to proactive communication in AI-agents using contextual factors. Proactive communication was learned in two consecutive experimental steps: (a) multi-agent team simulations to learn effective communicative behaviors, and (b) human-agent team experiments to refine communication suitable for a human team member. Results consist of proactive communication policies for communicating both beliefs and goals within human-agent teams. Agents learned to use minimal communication to improve team performance in simulation, while they learned more specific socially desirable behaviors in the human-agent team experiment.

  • 49.
    Winikoff, Michael
    et al.
    Victoria University of Wellington, New Zealand.
    Sidorenko, Galina
    Halmstad University, Sweden.
    Dignum, Virginia
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Why Bad Coffee? Explaining BDI Agent Behaviour with Valuings (Extended Abstract)2022In: Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence / [ed] Luc De Raedt, International Joint Conferences on Artificial Intelligence , 2022, p. 5782-5786Conference paper (Refereed)
    Abstract [en]

    An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results.

  • 50.
    Yildiz, Eren
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dignum, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Incorporating Social Practices in Dialogue Systems2022In: Chatbot Research and Design: 5th International Workshop, CONVERSATIONS 2021, Virtual Event, November 23–24, 2021, Revised Selected Papers / [ed] Asbjørn Følstad; Theo Araujo; Symeon Papadopoulos; Effie L.-C. Law Ewa Luger Morten Goodwin Petter Bae Brandtzaeg, Springer, 2022, p. 108-123Conference paper (Refereed)
    Abstract [en]

    Current dialogue management systems do not take social concepts such as norms, conventions, roles etc. into account when managing dialogues. Neither do they keep track of the personal (mental) state such as goals, needs, etc. While the data-driven approaches work quite well in some cases, they are usually domain/user dependent and not transparent. On the other hand, the rule-based methods can only work on the predefined scenarios and are not flexible in that sense. In addition, these approaches are limited to modeling only the dialogue system and do not include the human participant as part of the overall dialogue. This makes the current dialogue systems not well suited for complex and natural dialogues. In this paper, we present a dialogue management system framework that incorporates the notion of social practices as a first step to extend the type of dialogues that can be supported. The use of social practices is meant to give structure to the dialogue without restricting it to a fixed protocol. We demonstrate the use of the proposed system on a scenario between the doctor and patient roles where the doctor is a medical student and the patient is simulated by the dialogue management system.

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