Actes communicatifs à effets institutionnels

Cet article présente un cadre logique général pour représenter des actes de langage ayant des effets institutionnels. Il s'appuie sur les concepts de la théorie des actes de langage et complète la formalisation adoptée par l'organisme FIPA pour standardiser son langage de communication inter-agent. La caractéristique fondamentale de notre approche est que la force illocutoire de tous les actes de langage ainsi définis est déclarative. Le langage formel proposé pour exprimer le contenu propositionnel offre un grand pouvoir expressif et permet de représenter une grande variété d'actes de langage tels que : donner un pouvoir, nommer, ordonner, déclarer, etc. A general logical framework is presented to represent speech acts that have institutional effects. It is based on the concepts of the Speech Act Theory and takes the form of the Agent Communication Language standardized by the FIPA organization. The most important feature of our approach is that the illocutionary force of all of these speech acts is declarative. The formal language that is proposed to express the propositional content has a large expressive power and makes it possible to represent a large variety of speech acts such as : to empower, to appoint, to order, to declare, etc

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

Automated reasoning in metabolic networks with inhibition

International audienceThe use of artificial intelligence to represent and reason about metabolic networks has been widely investigated due to the complexity of their imbrication. Its main goal is to determine the catalytic role of genomes and their interference in the process. This paper presents a logical model for metabolic pathways capable of describing both positive and negative reactions (activations and inhibitions) based on a fragment of first order logic. We also present a translation procedure that aims to transform first order formulas into quantifier free formulas, creating an efficient automated deduction method allowing us to predict results by deduction and infer reactions and proteins states by abductive reasoning

A framework for modelling Molecular Interaction Maps

Metabolic networks, formed by a series of metabolic pathways, are made of intracellular and extracellular reactions that determine the biochemical properties of a cell, and by a set of interactions that guide and regulate the activity of these reactions. Most of these pathways are formed by an intricate and complex network of chain reactions, and can be represented in a human readable form using graphs which describe the cell cycle checkpoint pathways. This paper proposes a method to represent Molecular Interaction Maps (graphical representations of complex metabolic networks) in Linear Temporal Logic. The logical representation of such networks allows one to reason about them, in order to check, for instance, whether a graph satisfies a given property $\phi$, as well as to find out which initial conditons would guarantee $\phi$, or else how can the the graph be updated in order to satisfy $\phi$. Both the translation and resolution methods have been implemented in a tool capable of addressing such questions thanks to a reduction to propositional logic which allows exploiting classical SAT solvers.Comment: 31 pages, 12 figure

Regression in Modal Logic

In this work we propose an encoding of Reiter’s Situation Calculus solution to the frame problem into the framework of a simple multimodal logic of actions. In particular we present the modal counterpart of the regression technique. This gives us a theorem proving method for a relevant fragment of our modal logic

Strategies for the computation of conditional answers

We consider bere non-Horn Deductive Data Bases {DDB). In this con­ text there are many queries whose answer is : I don't know. A first ap­proach to reduce the number of such answers is to add information, like default rules, in order to automatically generate assumptions. The second approach, which is adopted in this paper, is to provide to tbe user the con­ditions that guarantee the validity of the answer. These conditional answers are generated by standard reasoning, and not by default reasoníng. Then the problem is the following : if T represents the DDB and q the query, and iI there is no direct answer to q, we want to produce the more general conctitions c such that : T |- q <- c. We present two strategies, GASP and GALP, designed for this purpose. They are defined by meta rules, and the meta.rules can be used for a least fixpoint operator definition. We show that the GASP strategy is always more efficient than GALP, but the GALP strategy can be adapted in order to compute ground conditional answers. The least fucpoint operator associated to GRALP (the strategy adapted from GALP) computes the answer in a finite number of steps, even if the DDB contains recursive definitions

Integrating State Constraints and Obligations in Situation Calculus

The ramification problem concerns the characterisation of indirect effects of actions. This problem arises when a theory of action is integrated with a set of state constraints. So integrating state constraints to a solution of the frame problem must deal with the ramification problem. In the situation calculus a general solution to both the frame and ramification problems has been proposed. This solution includes the indirect effects of actions in the successor state axioms. On the other hand, in the situation calculus, the notion of belief fluents has been introduced in order to distinguish between facts that hold in a situation and facts that are believed to hold in a situation. So apart from the traditional frame and ramification problems, a belief counterpart of these problems is considered. The successor belief state axioms were proposed to address the belief frame problem. Inspired in the mentioned approaches, we propose a general solution to the belief frame and ramification problems. We consider two sorts of constraints: the believed state constraints relating to physical laws and the believed mental constraints relating to social laws. Constraints imposed by social laws are well know in literature as obligations. Automated reasoning based on the proposal could easily be implemented in Prolog. 1

An inference rule for hypothesis generation

There are many new application fields for automated deduction where we have to apply abductive reasoning. In these applications we have to generate consequences of a given theory having some appropriate properties. In particular we consider the case where we have to generate the clauses containing instances of a given literal L. The negation of the other literals in such clauses are hypothesis allowing to derive L. In this paper we present an inference rule, called L-inference, which was designed in order to derive those clauses, and a L-strategy. The L-inference rule is a sort of Input Hyperresolution. The main result of the paper is the proof of the soundness and completeness of the L-inference rule. The L-strategy associated to the L-inference rule, is a saturation by level with deletion of the tautologies and of the subsumed clauses. We show that the L-strategy is also complete.