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Jensen, M., Vanhée, L. & Dignum, F. (2024). Dynamic context-sensitive deliberation. In: Luis G. Nardin; Sara Mehryar (Ed.), Multi-Agent-Based simulation XXIV: 24th International workshop, MABS 2023 London, UK, May 29 – June 2, 2023 Revised selected papers. Paper presented at 24th International Workshop, MABS 2023, London, UK, May 29 - June 2, 2023 (pp. 112-126). Paper presented at 24th International Workshop, MABS 2023, London, UK, May 29 - June 2, 2023. Springer Nature
Open this publication in new window or tab >>Dynamic context-sensitive deliberation
2024 (English)In: 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.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Artificial Intelligence, ISSN 03029743, E-ISSN 16113349 ; 14558
Keywords
Decision Context, Deliberation, Realism, Scalability, Social agents
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-225518 (URN)10.1007/978-3-031-61034-9_8 (DOI)2-s2.0-85194088420 (Scopus ID)9783031610332 (ISBN)9783031610349 (ISBN)
Conference
24th International Workshop, MABS 2023, London, UK, May 29 - June 2, 2023
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

Included in the following conference series:

International Workshop on Multi-Agent Systems and Agent-Based Simulation

Available from: 2024-06-11 Created: 2024-06-11 Last updated: 2024-06-11Bibliographically approved
Gholizadeh Ansari, S., Prasetya, I., Dastani, M., Keller, G., Prandi, D., Kifetew, F. M. & Dignum, F. (2024). PX-MBT: A framework for model-based player experience testing. Science of Computer Programming, 236, Article ID 103108.
Open this publication in new window or tab >>PX-MBT: A framework for model-based player experience testing
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2024 (English)In: Science of Computer Programming, ISSN 0167-6423, E-ISSN 1872-7964, Vol. 236, article id 103108Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Agent-based testing, Emotion modeling, Model-based testing, PX testing
National Category
Computer Systems Computer Sciences
Identifiers
urn:nbn:se:umu:diva-223837 (URN)10.1016/j.scico.2024.103108 (DOI)2-s2.0-85189754785 (Scopus ID)
Funder
EU, Horizon 2020, 856716
Available from: 2024-04-30 Created: 2024-04-30 Last updated: 2024-04-30Bibliographically approved
Lorig, F., Vanhée, L. & Dignum, F. (2023). Agent-based social simulation for policy making. In: Human-centered artificial intelligence: Advanced lectures. Paper presented at 18th European Advanced Course on Artificial Intelligence, ACAI 2021, Berlin, Germany, October 11-15, 2021 (pp. 391-414). Springer Nature
Open this publication in new window or tab >>Agent-based social simulation for policy making
2023 (English)In: Human-centered artificial intelligence: Advanced lectures, Springer Nature, 2023, p. 391-414Conference paper, Published 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.

Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13500
Keywords
Agent-based modeling, Analysis of simulation outputs, Interaction with stakeholders, NetLogo, Simulation for crisis situations, Sophisticated agent architectures
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-206964 (URN)10.1007/978-3-031-24349-3_20 (DOI)2-s2.0-85152526853 (Scopus ID)9783031243486 (ISBN)
Conference
18th European Advanced Course on Artificial Intelligence, ACAI 2021, Berlin, Germany, October 11-15, 2021
Note

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Conference series: ACAI: ECCAI Advanced Course on Artificial Intelligence

Available from: 2023-04-26 Created: 2023-04-26 Last updated: 2023-04-26Bibliographically approved
Kammler, C., Mellema, R. & Dignum, F. (2023). Agents dealing with norms and regulations. In: Fabian Lorig; Emma Norling (Ed.), Multi-agent-based simulation XXIII: 23rd International Workshop, MABS 2022, virtual event, May 8-9, 2022: Revised selected papers. Paper presented at 23rd International Workshop on Multi-Agent-Based Simulation, MABS 2022, collocated with the International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2022, virtual event, May 8-9, 2022. (pp. 134-146). Springer Science+Business Media B.V.
Open this publication in new window or tab >>Agents dealing with norms and regulations
2023 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2023
Series
Lecture notes in artificial intelligence, ISSN 03029743, E-ISSN 16113349 ; 13743
Keywords
Needs, Normative reasoning, Social simulation, Values
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-205476 (URN)10.1007/978-3-031-22947-3_11 (DOI)000972616600011 ()2-s2.0-85148692509 (Scopus ID)9783031229466 (ISBN)978-3-031-22947-3 (ISBN)
Conference
23rd International Workshop on Multi-Agent-Based Simulation, MABS 2022, collocated with the International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2022, virtual event, May 8-9, 2022.
Available from: 2023-03-17 Created: 2023-03-17 Last updated: 2023-09-05Bibliographically approved
Gentile, M., Città, G., Marfisi-Schottman, I., Dignum, F. & Allegra, M. (2023). Editorial: Artificial intelligence for education. Frontiers in Education, 8, Article ID 1276546.
Open this publication in new window or tab >>Editorial: Artificial intelligence for education
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2023 (English)In: Frontiers in Education, E-ISSN 2504-284X, Vol. 8, article id 1276546Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Frontiers Media S.A., 2023
Keywords
Artificial Intelligence and Education (AIED), education, generative AI, intelligent tutor systems, learning processes
National Category
Pedagogy
Identifiers
urn:nbn:se:umu:diva-217210 (URN)10.3389/feduc.2023.1276546 (DOI)2-s2.0-85177479739 (Scopus ID)
Available from: 2023-11-29 Created: 2023-11-29 Last updated: 2023-11-29Bibliographically approved
den Hurk, M. v., Dechesne, M. & Dignum, F. (2023). First step towards a new understanding of radicalisation: modeling identity fusion. In: Flaminio Squazzoni (Ed.), Advances in social simulation: Proceedings of the 17th Social Simulation Conference, European Social Simulation Association. Paper presented at 17th annual conference of European Social Simulation Association, ESSA 2022, Milan, Italy, September 12-16, 2022 (pp. 223-234). Springer Nature
Open this publication in new window or tab >>First step towards a new understanding of radicalisation: modeling identity fusion
2023 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Springer Proceedings in Complexity, ISSN 2213-8684, E-ISSN 2213-8692
Keywords
Agent-based modeling, Identity fusion, Personal identity, Pro-group behaviour, Social identity
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-215964 (URN)10.1007/978-3-031-34920-1_18 (DOI)2-s2.0-85174488172 (Scopus ID)978-3-031-34919-5 (ISBN)978-3-031-34922-5 (ISBN)978-3-031-34920-1 (ISBN)
Conference
17th annual conference of European Social Simulation Association, ESSA 2022, Milan, Italy, September 12-16, 2022
Available from: 2023-10-30 Created: 2023-10-30 Last updated: 2023-10-30Bibliographically approved
Baum, K., Bryson, J., Dignum, F., Dignum, V., Grobelnik, M., Hoos, H., . . . Vinuesa, R. (2023). From fear to action: AI governance and opportunities for all. Frontiers in Computer Science, 5, Article ID 1210421.
Open this publication in new window or tab >>From fear to action: AI governance and opportunities for all
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2023 (English)In: Frontiers in Computer Science, E-ISSN 2624-9898, Vol. 5, article id 1210421Article in journal (Other academic) Published
Place, publisher, year, edition, pages
Frontiers Media S.A., 2023
Keywords
Artificial Intelligence, generative AI, governance, large language models, responsible AI, Trustworthy AI
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-209884 (URN)10.3389/fcomp.2023.1210421 (DOI)2-s2.0-85161079950 (Scopus ID)
Available from: 2023-06-15 Created: 2023-06-15 Last updated: 2023-06-15Bibliographically approved
Ansari, S. G., Prasetya, I., Prandi, D., Kifetew, F. M., Dastani, M., Dignum, F. & Keller, G. (2023). Model-based player experience testing with emotion pattern verification. In: Leen Lambers; Sebastián Uchitel (Ed.), 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. Paper presented at 26th International Conference on Fundamental Approaches to Software Engineering, FASE 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023, April 22-27, 2023. (pp. 151-172). Springer Science+Business Media B.V.
Open this publication in new window or tab >>Model-based player experience testing with emotion pattern verification
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2023 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2023
Series
Lecture Notes in Computer Science , ISSN 03029743, E-ISSN 16113349 ; 13991
Keywords
agent-based testing, automated player experience testing, model-based testing, models of emotion
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-210199 (URN)10.1007/978-3-031-30826-0_9 (DOI)2-s2.0-85161368617 (Scopus ID)9783031308253 (ISBN)978-3-031-30826-0 (ISBN)
Conference
26th International Conference on Fundamental Approaches to Software Engineering, FASE 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023, April 22-27, 2023.
Available from: 2023-06-28 Created: 2023-06-28 Last updated: 2023-06-28Bibliographically approved
Mathieu, P., Dignum, F., Novais, P. & De la Prieta, F. (2023). Preface. In: Philippe Mathieu; Frank Dignum; Paulo Novais; Fernando De la Prieta (Ed.), 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. Springer Nature
Open this publication in new window or tab >>Preface
2023 (English)In: 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)
Place, publisher, year, edition, pages
Springer Nature, 2023
Series
Lecture notes in artifical intelligence, ISSN 0302-9743, E-ISSN 1611-3349 ; 13955
Identifiers
urn:nbn:se:umu:diva-214050 (URN)2-s2.0-85169054647 (Scopus ID)978-3-031-37615-3 (ISBN)978-3-031-37616-0 (ISBN)
Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2023-09-06Bibliographically approved
Dignum, F. (2023). Should we make predictions based on social simulations?. International Journal of Social Research Methodology, 26(2), 193-206
Open this publication in new window or tab >>Should we make predictions based on social simulations?
2023 (English)In: International Journal of Social Research Methodology, ISSN 1364-5579, E-ISSN 1464-5300, Vol. 26, no 2, p. 193-206Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Routledge, 2023
Keywords
agent-based modeling, COVID-19, policy making, Predictions, validity
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-203128 (URN)10.1080/13645579.2022.2137925 (DOI)000870587800001 ()2-s2.0-85140341633 (Scopus ID)
Available from: 2023-01-16 Created: 2023-01-16 Last updated: 2023-07-14Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5103-8127

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