Grounding power on actions and mental attitudes

International audienceThe main objective of this work is to develop a logic called IAL (Intentional Agency Logic) in which we can reason about mental states of agents, action occurrences, and agentive and group powers. IAL will be exploited for a formal analysis of different forms of power such as an agent i's power of achieving a certain result and an agent i's power over another agent j (alias social power)

Comodo: Collaborative Monitoring of Commitment Delegations

Understanding accountability in contract violations, e.g., whom is accountable for what, is a tedious, time-consuming, and costly task for human decision-making, especially when contractual responsibilities are delegated among parties. Intelligent software agents equipped with expert capabilities such as monitoring and diagnosis help save time and improve accuracy of diagnosis by formal reasoning upon electronic contracts. Such contracts are represented as commitment norms, a well studied artifact in multi-agent systems, which provide semantics for agent interactions. Due to the open and heterogeneous nature of multi-agent systems, commitments are often violated. When a commitment is violated, e.g., an exception occurs, agents need to collaborate to understand what went wrong and which agent is responsible. We propose Comodo: a framework for monitoring commitment delegations and detecting violations. We define a complete set of possible rational delegation schemes for commitments, identifying for each combination of delegations what critical situations may lead to an improper delegation and potentially to a commitment violation. Comodo provides a sound and complete distributed reasoning procedure that is able to find all improper delegations of a given commitment. We provide the complete implementation of Comodo using the Reactive Event Calculus, and present an e-commerce case study to demonstrate its workings. Due to its generic nature, we discuss the application of our approach to other distributed diagnosis problems in emergency healthcare, Internet of Things and smart environments, and security, privacy, and accountability in the context of socio-technical system

A Study of Agent Influence in Nested Agent Interactions

This work develops a theory of agent influence and applies it to a coached system of simple reactive agents. Our notion of influence is intended to describe agent ability which is contingent on the actions of other agents and we view such behaviours as being “nested”. An agent may have the ability to make A hold only if another agent has carried out a particular action. Our analysis of this is based on a combination of the observation of the effects of an agent’s actions in a bounded environment and observations on what may be changed in that environment and is intended to allow for a logical representation of nested behaviours. We build on this notion to develop a theory of influence which we offer as an extension of existing systems for representing agency and its effects. The notion of an agent being able to “see to it” that something is brought about has been a useful device for reasoning about agent ability. These so-called STIT semantics have been developed by a number of researchers. Standard STIT semantics allow statements of the form [α stit: A] which says that agent a has the ability to see to it that A holds. Although based on the concept of agent action STIT semantics also allow for the representation of concepts involving what may be thought of as inaction. An agent deciding, for example, not to execute a particular action may be characterised as seeing to it that it does not see to it that A, [α stit: [α stit: -A]]. STIT encourages nesting and although this nesting extends across actions within an agent it does not extend easily across agents. So called other agent statements of the form [β stit: [α stit: A]] do not make sense in standard stit semantics because β seeing to it that α sees to it that A holds implies that β has some dominion over a which, in turn, compromises α’s agency. Although the statement makes no sense under standard STIT it does make sense in an intuitive way and Brian Chellas [31] notes that it would be: “...bizarre to deny that an agent should be able to see to it that another agent sees to something” This is also mentioned in Belnap et al. [8, page 275]. Chellas is correct and there are numerous settings in which other agent STIT does make sense. These settings, which are captured in various readings of STIT, may bring a great deal of system level overhead. In a normative system, for example, β may have the option of imposing a sanction on α if α fails to bring about A and in this sense may be thought of as seeing to it that α sees to it that A holds. Similarly a deontic reading may place β in a position where it is able to place an obligation on α to bring about A. These readings allow for sensible interpretation of other agent STIT but the examples above require that agents have sufficient awareness of personal utility be able to manage sanctions or that they are able to reason about obligations. These readings offer nothing for simple agents with limited resources and abilities. We offer another reading for the STIT element, one based on the concept of agent influence and one which carries minimal system level overhead. Because influence may be contingent on simultaneous or sequential behaviour by a number of agents it is extendible across agents and offers a means of addressing other agent statements. We extend the standard STIT semantics of Horty, Belnap and others with the introduction of “leads to” and “may lead to” operators which allow us to move our analysis into a setting where observation provides evidence of influence. We then explore the manifestation of influence in a number of scenarios. After exploring how influence manifests itself we then offer a partial logical characterisation of the influence operators and discuss its relationship with standard STIT. Building on these semantics and the partial logical characterisation we then explore the practical use of our theory of influence in an agent learning system. We describe experiments with a system specified by safety and liveness properties and having two broad classes of agents, actors and coaches. Actor agents will manipulate their environment and coaching agents will observe the actor’s behaviour and its effects using aggregated observations to generate new behaviours which are then seeded in the environment to modify actor behaviour. We then offer a discussion and evaluation of our theory and its applications indicating where it may be further developed and applied

Modèle multi-agents pour le filtrage collaboratif de l'information

Les systèmes de recommandation sont nés de la volonté de pallier le problème de surcharge d'information du web. Combinant des techniques de filtrage d'information, personnalisation, intelligence artificielle, réseaux sociaux et interaction personne-machine, les systèmes de recommandation fournissent à des utilisateurs des suggestions qui répondent à leurs besoins et préférences informationnelles. En effet, les systèmes de recommandation sont particulièrement sollicités dans les applications de commerce électronique. Cependant, ce type de système a été en grande partie confiné à une architecture centralisée. Récemment, l'architecture distribuée a connu une popularité croissante, comme en témoigne par exemple, les réseaux pair-à-pair (« peer-to-peer »), le calcul distribué (« Grid computing »), le web sémantique, etc., et s'impose peu à peu comme une alternative à l'approche client/serveur classique. L'hypothèse des chercheurs est que les systèmes de recommandation peuvent tirer profit d'une architecture distribuée. Dans cette thèse, nous étudions les défis que posent les systèmes de recommandation distribués et nous proposons une nouvelle architecture pair-à-pair, de filtrage collaboratif, basée sur la discrimination du voisinage. Nous étudions l'évolution de la performance, de la couverture et de la qualité des prédictions pour différentes techniques de recommandation. En outre, nous identifions la méthode de recommandation la plus efficace pour cette nouvelle architecture pair-à-pair. Bien que cette thèse se concentre essentiellement sur le domaine décentralisé de système de recommandation, nos contributions ne se limitent pas strictement à ce domaine de recherche. En effet, ces contributions touchent des problèmes de recherche dans plusieurs autres domaines de recherche (système multi-agents, gestions profils utilisateurs, réduction de la complexité computationnelle, collecte des préférences utilisateurs, PageRank, etc.). ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Filtrage de l'information, Filtrage collaboratif, Système de recommandation, Système distribué, Agent social

Delegation and mental states

Short paperInternational audienceIn the recent literature on multiagent systems there have been several proposals of formal systems for reasoning about delegation. Most of these approaches have dealt with the concept of delegation leaving mental states such as beliefs, goals and intentions out of consideration. The aim of this paper is to develop a formal approach for reasoning about delegation by modeling intentions and beliefs of the delegating agent in an explicit way. We present a logic where it is possible to investigate the relations between the concept of Intention to be and the concept of Delegation