Strategies for distributing goals in a team of cooperative agents

This paper addresses the problem of distributing goals to individual agents inside a team of cooperative agents. It shows that several parameters determine the goals of particular agents. The first parameter is the set of goals allocated to the team; the second parameter is the description of the real actual world; the third parameter is the description of the agents' ability and commitments. The last parameter is the strategy the team agrees on: for each precise goal, the team may define several strategies which are orders between agents representing, for instance, their relative competence or their relative cost. This paper also shows how to combine strategies. The method used here assumes an order of priority between strategie

Distribution of goals addressed to a group of agents

The problem investigated in this paper is the distribution of goals addressed to a group of rational agents. Those agents are characterized by their ability (i.e. what they can do), their knowledge about the world and their commitments. The goals of the group are represented by conditional preferences. In order to deduce the actual goals of the group, we determine its ability using each agent’s ability and we suppose that the agents share a common knowledge about the world. The individual goals of an agent are deduced using its ability, the knowledge it has about the world, its own commitments and the commitments of the other agents of the group

Deriving individual obligations from collective obligations

A collective obligation is an obligation directed to a group of agents so that the group, as a whole, is obliged to achieve a given task. The problem investigated here is the impact of collective obligations on individual obligations,i.e. obligations directed to single agents of the group. In this case, we claim that the derivation of individual obligations from collective obligations depends on several parameters among which the ability of the agents (i.e. what they can do) and their own personal commitments (i.e. what they are determined to do). As for checking if these obligations are fulfilled or not, we need to know what are the actual actions performed by the agents

Desires, norms and constraints

This paper deals with modeling mental states of a rational agent, in particular states based on agent’s desires. It shows that the world the agent belongs to forces it to restrict its desires. More precisely, desires of a rational agent are restricted by the constraints that exist in the world and which express what is possible or necessary. Furthermore, if the agent is law-abiding, its desires are restricted by the regulations that are defined in the world and which express what is obligatory, permitted or forbidden. This paper characterizes how desires are restricted depending on the fact that the agent is law-abiding or not. This work considers the general case when the agent orders its own desires according to a preference order. The solution is based on modeling desires, regulations and constraints in an unique formal system which is a logic of conditional preferences

A modal logic for reasoning on consistency and completeness of regulations

In this paper, we deal with regulations that may exist in multi-agent systems in order to regulate agent behaviour and we discuss two properties of regulations, that is consistency and completeness. After defining what consistency and completeness mean, we propose a way to consistently complete incomplete regulations. In this contribution, we extend previous works and we consider that regulations are expressed in a first order modal deontic logic

How to Complete Regulations in Multi-agent Systems

In this paper, we deal with regulations that may exist in multiagent systems in order to regulate agent behaviour. More precisely, we discuss two properties of regulations, consistency and ompleteness. After defining what consistency and completeness mean, we propose a way to consistently complete incomplete regulations. This contribution considers that regulations are expressed in a first order deontic logic. We will focus on particular regulations: information exchange policies

Agents coopératifs et politiques d'échanges d'informations

National audienceDans les systèmes multiagents, les agents sont souvent supposés être coopératifs les uns avec les autres dans leurs échanges, ceci afin de mener à bien une tâche globale. Ils sont également souvent tenus de respecter la politique d'échange d'informations du système qui régule quels échanges sont obligatoires, permis ou interdits entre les agents et sous quelles conditions. Comment dans ce cas les agents peuvent-ils être à la fois coopératifs et obéissants ? Dans cet article, nous définissons une politique d'échange d'informations particulière, que nous appelons politique de coopération, qui est la politique que les agents doivent respecter pour être coopératifs. Ainsi, nous ramenons la problématique d'être à la fois obéissant et coopératif à la problématique de respecter deux politiques d'échange d'informations différentes : la politique qui existe déjà au sein du système et la politique de coopération. Nous étudions également le cas où ces politiques sont conflictuelles et proposons alors de nouvelles définitions des caractères obéissants et coopératifs des agents

Reasoning about the safety of information: from logical formalization to operational definition

We assume that safety of information stored in a database depends on the reliability of the agents who have performed the insertions in the database. We present a logic S to represent information safety, and to derive answers to standard queries and to safety queries. The design of this logic is based on signaling act theory. Two strong simplifications lead to a logic S" with two modalities to represent explicit beliefs and implicit beliefs. Then, we present an operational view of S" in terms of First Order Logic, with meta predicates, which is implemented by a Prolog meta program. lt is proved that answers derived in S" and computed by the meta program are identical. This property gives a clea.r meaning to computed answers. Content areas: Epistemological foundations, Theorem proving, Logic programming, Multi-agent systems

Situation awareness and ability in coalitions

This paper proposes a discussion on the formal links between the Situation Calculus and the semantics of interpreted systems as far as they relate to Higher-Level Information Fusion tasks. Among these tasks Situation Analysis require to be able to reason about the decision processes of coalitions. Indeed in higher levels of information fusion, one not only need to know that a certain proposition is true (or that it has a certain numerical measure attached), but rather needs to model the circumstances under which this validity holds as well as agents' properties and constraints. In a previous paper the authors have proposed to use the Interpreted System semantics as a potential candidate for the unification of all levels of information fusion. In the present work we show how the proposed framework allow to bind reasoning about courses of action and Situation Awareness. We propose in this paper a (1) model of coalition, (2) a model of ability in the situation calculus language and (3) a model of situation awareness in the interpreted systems semantics. Combining the advantages of both Situation Calculus and the Interpreted Systems semantics, we show how the Situation Calculus can be framed into the Interpreted Systems semantics. We illustrate on the example of RAP compilation in a coalition context, how ability and situation awareness interact and what benefit is gained. Finally, we conclude this study with a discussion on possible future works

Exigences, réglementations et contraintes

Cet article s'intéresse à la modélisation des exigences et à l'expression de leur compatibilité avec une réglementation et des contraintes du domaine. Nous nous plaçons dans le cas où les exigences sont ordonnées selon un ordre de priorité. Le problème est alors de déterminer, parmi les exigences ordonnées de l'agent, les plus préférées qui sont compatibles avec la réglementation et avec les contraintes du domaine. Pour cela, nous proposons de modéliser les exigences, les réglementations et les contraintes dans un cadre formel unique, une logique de préférences conditionnelles. Le choix d'un formalisme unique nous permet de donner une caractérisation simple des meilleures exigences compatibles avec la réglementation et les contraintes