A finer grained modeling of rational coalitions using goals

We propose an extension of Coalitional ATL (a logic for reasoning about coalitions and their formation process, see [10]) by goals. This goal framework allows for a finer grained modeling of coalitions: Coalitional frameworks, based on Dungs’s abstract argumentation framework, are used to point out conflicts between agents, and goals refer to agents’ subjective incentives to join (or not to join) coalitions. We focus on two different aspects for cooperation allowing a more practical modeling of systemsWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

A finer grained modeling of rational coalitions using goals

We propose an extension of Coalitional ATL (a logic for reasoning about coalitions and their formation process, see [10]) by goals. This goal framework allows for a finer grained modeling of coalitions: Coalitional frameworks, based on Dungs’s abstract argumentation framework, are used to point out conflicts between agents, and goals refer to agents’ subjective incentives to join (or not to join) coalitions. We focus on two different aspects for cooperation allowing a more practical modeling of systemsWorkshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Formal methods for analysing, coordinating, and controlling decisions in multi-agent systems

Multiagentensysteme sind verteilte (Computer)Systeme, die sich aus autonomen interagierenden Systemkomponenten, bezeichnet als Agenten, zusammensetzen. Sie bieten ein flexibles Framework zur Modellierung und Analyse von interaktiven Systemen, in denen Kooperation, Eigeninteresse und Autonomie eine entscheidende Rolle spielen. Dies ist zum Beispiel der Fall in Smart Grids. Eine Herausforderung in solchen Systemen ist die Kontrolle und die Koordination von Systemausführungen. Agenten handeln autonom und lassen sich daher oftmals nicht direkt kontrollieren, sondern bestenfalls beeinflussen. Aufgrund der Autonomie und des Selbstinteresses, ist es schwierig, angemessene Kontrollmechanismen zu finden. Die vorliegende Arbeit behandelt formale Grundlagen zu den Themen Entscheidungsfindung, Koordination und Kontrolle in Multiagentensystemen. Insbesondere werden in diesem Zusammenhang Logiken zur Analyse und Spezifikation von strategischen Fähigkeiten von Agenten, unter diversen Restriktionen, untersucht. Es werden formale Ansätze zur Beeinflussung und Überwachung von Systemausführungen eingeführt. In einem weiteren Teil der Arbeit wird mittels spieltheoretischer Verfahren analysiert, wie rationale Agenten interagieren und Entscheidungen treffen. Es wird argumentiert, dass formale Methoden und Werkzeuge zur Analyse und Kontrolle von autonomen Systemen entscheidend für deren verlässliche Entwicklung sind.Multi-agent systems (MASs) are distributed (computer) systems composed of autonomously (inter-)acting system components referred to as agents. MASs offer a flexible framework to model and analyse many real world settings in which cooperation, self-interest, and autonomy are crucial elements. A key challenge in such settings is the control and coordination of behavior. However, due to the agents' autonomy behavior can often not be controlled, but at best be influenced in some way or another. For example, agents can be given incentives in order to affect their decision-making in such a way that the emergent behavior of all actors is desirable from the system's perspective. The properties of self-interest and autonomy make it challenging to find appropriate control mechanisms. Existing coordination and control approaches from the distributed system literature are often not applicable due to the lack of direct control on the system components of MASs. New methods and tools are needed. In this thesis formal foundations related to the subjects of decision making, coordination and control in MASs are studied. In particular, we investigate (extensions of) temporal and strategic logics which capture specific capabilities of agents that influence their decision making. We also propose formal approaches to control, coordinate and monitor the emergent behavior in MASs. In the last part of the thesis we analyse how rational agents interact and make decisions using game theoretical methods. We argue that such formal approaches and tools to analyse and control autonomous systems are crucial for the development of reliable and flexible systems and will become even more crucial in the near future

Seeing, Knowing, doing : case studies in modal logic

Dans le domaine des jeux vidéos par exemple, surtout des jeux de rôles, les personnages virtuels perçoivent un environnement, en tirent des connaissances puis effectuent des actions selon leur besoin. De même en robotique, un robot perçoit son environnement à l'aide de capteurs/caméras, établit une base de connaissances et effectuent des mouvements etc. La description des comportements de ces agents virtuels et leurs raisonnements peut s'effectuer à l'aide d'un langage logique. Dans cette thèse, on se propose de modéliser les trois aspects "voir", "savoir" et "faire" et leurs interactions à l'aide de la logique modale. Dans une première partie, on modélise des agents dans un espace géométrique puis on définit une relation épistémique qui tient compte des positions et du regard des agents. Dans une seconde partie, on revisite la logique des actions "STIT" (see-to-it-that ou "faire en sorte que") qui permet de faire la différence entre les principes "de re" et "de dicto", contrairement à d'autres logiques modales des actions. Dans une troisième partie, on s'intéresse à modéliser quelques aspects de la théorie des jeux dans une variante de la logique "STIT" ainsi que des émotions contre-factuelles comme le regret. Tout au long de cette thèse, on s'efforcera de s'intéresser aux aspects logiques comme les complétudes des axiomatisations et la complexité du problème de satisfiabilité d'une formule logique. L'intégration des trois concepts "voir", "savoir" et "faire" dans une et une seule logique est évoquée en conclusion et reste une question ouverte.Agents are entities who perceive their environment and who perform actions. For instance in role playing video games, ennemies are agents who perceive some part of the virtual world and who can attack or launch a sortilege. Another example may concern robot assistance for disabled people: the robot perceives obstacles of the world and can alert humans or help them. Here, we try to give formal tools to model knowledge reasoning about the perception of their environment and about actions based, on modal logic. First, we give combine the standard epistemic modal logic with perception constructions of the form (agent a sees agent b). We give a semantics in terms of position and orientation of the agents in the space that can be a line (Lineland) or a plane (Flatland). Concerning Lineland, we provide a complete axiomatization and an optimal procedure for model-checking and satisfiability problem. Concerning Flatland, we show that both model-checking and satisfiability problem are decidable but the exact complexities and the axiomatization remain open problems. Thus, the logics of Lineland and Flatland are completely a new approach: their syntax is epistemic but their semantics concern spatial reasoning. Secondly, we study on the logic of agency ``see-to-it-that'' STIT made up of construction of the form [J]A standing for ``the coalition of agents J sees to it that A''. Our interest is motivated: STIT is strictly more expressive that standard modal logic for agency like Coalition Logic CL or Alternating-time Temporal Logic ATL. In CL or ATL the ``de re'' and ``de dicto'' problem is quite difficult and technical whereas if we combine STIT-operators with epistemic operators, we can solve it in a natural way. However this strong expressivity has a prize: the general version of STIT is undecidable. That is why we focus on some syntactic fragments of STIT: either we restrict the allowed coalitions J in constructions [J]A or we restrict the nesting of modal STIT-operators. We provide axiomatizations and complexity results. Finally, we give flavour to epistemic modal logic by adding STIT-operators. The logic STIT is suitable to express counterfactual statements like ``agent a could have choosen an action such that A have been true''. Thus we show how to model counterfactual emotions like regret, rejoicing, disappointment and elation in this framework. We also model epistemic games by adapting the logic STIT by giving explicitely names of actions in the language. In this framework, we can model the notion of rational agents but other kind of behaviour like altruism etc., Nash equilibrium and iterated deletion of strictly dominated strategies

COIN@AAMAS2015

COIN@AAMAS2015 is the nineteenth edition of the series and the fourteen papers included in these proceedings demonstrate the vitality of the community and will provide the grounds for a solid workshop program and what we expect will be a most enjoyable and enriching debate.Peer reviewe