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  • 1.
    Kampik, Timotheus
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Empathic Agents: A Hybrid Normative/Consequentialistic Approach2019Ingår i: AAMAS 2019, ASSOC COMPUTING MACHINERY , 2019, s. 2423-2425Konferensbidrag (Refereegranskat)
    Abstract [en]

    Complex information systems operate with increasing degrees of autonomy. Consequently, such systems should not only optimize for simple metrics (like clicks and views) that reflect the system provider's preferences but also consider norms or rules, as well as the preferences of other agents that are affected by the systems' actions. As a means to achieve such behavior, we propose the design and development of empathic agents that use a mixed rule/utility-based approach when deciding on how to act, considering both their own and others' utility functions. The agents make use of formal argumentation to reach an agreement on how to act in case of inconsistent beliefs. A promising domain for applying our empathic agents is recommender systems.

  • 2.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Signavio GmbH, Berlin, Germany.
    Najjar, Amro
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. AI-Robolab/ICR, Computer Science and Communications, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
    Integrating Multi-agent Simulations into Enterprise Application Landscapes2019Ingår i: Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. PAAMS 2019 / [ed] De La Prieta F. et al., 2019, s. 100-111Konferensbidrag (Refereegranskat)
    Abstract [en]

    To cope with increasingly complex business, political, and economic environments, agent-based simulations (ABS) have been proposed for modeling complex systems such as human societies, transport systems, and markets. ABS enable experts to assess the influence of exogenous parameters (e.g., climate changes or stock market prices), as well as the impact of policies and their long-term consequences. Despite some successes, the use of ABS is hindered by a set of interrelated factors. First, ABS are mainly created and used by researchers and experts in academia and specialized consulting firms. Second, the results of ABS are typically not automatically integrated into the corresponding business process. Instead, the integration is undertaken by human users who are responsible for adjusting the implemented policy to take into account the results of the ABS. These limitations are exacerbated when the results of the ABS affect multi-party agreements (e.g., contracts) since this requires all involved actors to agree on the validity of the simulation, on how and when to take its results into account, and on how to split the losses/gains caused by these changes. To address these challenges, this paper explores the integration of ABS into enterprise application landscapes. In particular, we present an architecture that integrates ABS into cross-organizational enterprise resource planning (ERP) processes. As part of this, we propose a multi-agent systems simulator for the Hyperledger blockchain and describe an example supply chain management scenario type to illustrate the approach.

  • 3.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Najjar, Amro
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. AI-Robolab/ICR Computer Science and Communications University of Luxembourg Esch-sur-Alzette, Luxembourg.
    Technology-facilitated Societal Consensus2019Ingår i: UMAP'19 Adjunct: Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, Larnaca, Cyprus: ACM Digital Library, 2019, s. 3-7Konferensbidrag (Refereegranskat)
    Abstract [en]

    The spread of radical opinions, facilitated by homophilic Internet communities (echo chambers), has become a threat to the stability of societies around the globe. The concept of choice architecture-the design of choice information for consumers with the goal of facilitating societally beneficial decisions-provides a promising (although not uncontroversial) general concept to address this problem. The choice architecture approach is reflected in recent proposals advocating for recommender systems that consider the societal impact of their recommendations and not only strive to optimize revenue streams. However, the precise nature of the goal state such systems should work towards remains an open question. In this paper, we suggest that this goal state can be defined by considering target opinion spread in a society on different topics of interest as a multivariate normal distribution; i.e., while there is a diversity of opinions, most people have similar opinions on most topics. We explain why this approach is promising, and list a set of cross-disciplinary research challenges that need to be solved to advance the idea.

  • 4.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Najjar, Amro
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Calvaresi, Davide
    University of Applied Science Western Switzerland.
    MAS-Aided Approval for Bypassing Decentralized Processes: an Architecture2018Ingår i: 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), IEEE Computer Society, 2018, s. 713-718Konferensbidrag (Refereegranskat)
    Abstract [en]

    Executing business processes in a decentralized manner can improve inter-organizational efficacy. For example, blockchain-based process execution allows, at least conceptually, for cross-organizational compatibility, data integration, and integrity assurance without the need for a centralized trusted operator. However, most business processes run in agile and rapidly changing business environments. Updating a decentralized process requires continuous and extensive consensus-building efforts. Reflecting all organizations' business requirements is hardly practicable. Hence, in many real-life scenarios, to support cases with initially unforeseen properties, organizations can allow to bypass the decentralized process and fall-back to local variants. Yet, the decision to bypass or update a given process can have significant social implications since it may encourage a social dynamic that encourages collective avoidance of the decentralized process. This paper proposes a multi-agent simulation system to assess the social consequences of approving a bypass under given conditions. The proposed simulation is intended to inform the decision-maker (human or machine) on whether to allow to bypass a process or not. Moreover, we present an architecture for the integration of multi-agent simulation system, local process engine, and decentralized process execution environment, and describe a possible implementation with a particular tool chain.

  • 5.
    Kampik, Timotheus
    et al.
    Umeå universitet.
    Nieves, Juan Carlos
    Umeå universitet.
    JS-son - A Minimal JavaScript BDI Agent Library2019Ingår i: EMAS 2019: Accepted Papers, Centre for Autonomous systems technology, University of Liverpool , 2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    There is a multitude of agent-oriented software engineering frame-works available, most of them produced by the academic multi-agent systemscommunity. However, these frameworks often impose programming paradigmson their users that are hard to learn for engineers who are used to modern high-level programming languages such as JavaScript and Python. To show how theadoption of agent-oriented programming by the software engineering mainstreamcan be facilitated, we provide an early, simplistic JavaScript library prototype forimplementing belief-desire-intention (BDI) agents. The library focuses on thecore BDI concepts and refrains from imposing further restrictions on the pro-gramming approach. To illustrate its usefulness, we demonstrate how the librarycan be used for multi-agent systems simulations on the web, as well as embeddedin Python-based data science tools.

  • 6.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindgren, Helena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Coercion and deception in persuasive technologies2018Ingår i: Proceedings of the 20th International Trust Workshop / [ed] Robin Cohen, Murat Sensoy, Timothy J. Norman, CEUR-WS , 2018, s. 38-49Konferensbidrag (Refereegranskat)
    Abstract [en]

    Technologies that shape human behavior are of high societal relevance, both when considering their current impact and their future potential. In information systems research and in behavioral psychology, such technologies are typically referred to as persuasive technologies. Traditional definitions like the ones created by Fogg, and Harjumaa and Oinas-Kukkonen, respectively, limit the scope of persuasive technology to non-coercive, non-deceptive technologies that are explicitly designed for persuasion. In this paper we analyze existing technologies that blur the line between persuasion, deception,and coercion. Based on the insights of the analysis, we lay down an updated definition of persuasive technologies that includes coercive and deceptive forms of persuasion. Our definition also accounts for persuasive functionality that was not designed by the technology developers. We argue that this definition will help highlight ethical and societal challenges related to technologies that shape human behavior and encourage research that solves problems with technology-driven persuasion. Finally, we suggest multidisciplinary research that can help address the challenges our definition implies. The suggestions we provide range from empirical studies to multi-agent system theory.

  • 7.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindgren, Helena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Empathic autonomous agents2019Ingår i: Engineering multi-agent systems: 6th international workshop, EMAS 2018, Stockholm, Sweden, July 14-15, 2018, revised selected papers / [ed] Danny Weyns, Viviana Mascardi and Alessandro Ricci, Cham: Springer, 2019, 6, s. 181-201Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to arise in non-human agent-to-agent interaction. We introduce a theoretical framework for an empathic autonomous agent that proactively identifies potential conflicts of interests in interactions with other agents (and humans) by considering their utility functions and comparing them with its own preferences using a system of shared values to find a solution all agents consider acceptable. To illustrate how empathic autonomous agents work, we provide running examples and a simple prototype implementation in a general-purpose programing language. To give a high-level overview of our work, we propose a reasoning-loop architecture for our empathic agent.

  • 8.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindgren, Helena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Implementing Argumentation-enabled Empathic Agents2018Ingår i: Multi-Agent Systems: 16th European Conference, EUMAS 2018, Bergen, Norway, December 6–7, 2018, Revised Selected Papers / [ed] Slavkovik, Marija, Springer Berlin/Heidelberg, 2018, s. 140-155Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.

    Publikationen är tillgänglig i fulltext från 2020-01-01 00:00
  • 9.
    Kampik, Timotheus
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindgren, Helena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Towards empathic autonomous agents2018Ingår i: / [ed] Viviana Mascardi, Alessandro Ricci, Danny Weyns, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to arise in non-human agent-to-agent interaction. We work towards a theoretical framework for an empathic autonomous agent that proactively identifies potential conflicts of interests in interactions with other agents (and humans) byl earning their utility functions and comparing them with its own preferences using a system of shared values to find a solution all agents consider acceptable.To provide a high-level overview of our work, we propose a reasoning-loop architecture to address the problem in focus. To realize specific components of the architecture, we suggest applying existing concepts in argumentation and utility theory. Reinforcement learning methods can be used by the agent to learn from and interact with its environment.

1 - 9 av 9
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