Bruno Mermet

Goal decomposition tree: an agent model to generate a validated agent behaviour

This paper deals with a goal-oriented agent model called Goal Decomposition Tree (GDT) allowing both to specify and validate the behaviour of an agent. This work takes place in a global framework whose goal is to define a process allowing to start from a problem specification to obtain a validated implementation of a corresponding MAS. The GDT model has been used to specify a prey-predator system which has been verified this way.

Safe combinations of services using B

The paper reports on the use of the B method and related tools to handle the feature interaction problem in telecommunications. The feature interaction problem states critical questions with respect to safety, sociological and legal aspects. Our approach proposes a new way to combine abstract machines and evaluates the resulting generation of proof obligations. The B method is a framework for specifying, refining and developing systems in a mathematical and rigorous, but simple way, and services are specified in the B method. The feature interaction problem is modelled simply as a violation of an invariant. The B method is supported by sofware that helps the specifier of services and features. We have not only modeled services within the B technology, but we have also extended possibilities of B by combining abstract machines.

Incremental specification of telecommunication services

This paper presents the specification of telecommunication services using B abstract machines, and it defines the feature interaction problem as an interference issue among processes sharing common resources. The work reported is experimental in nature as we explore the way in which to use the B method to tackle the feature interaction problem in telecommunication services. The B method is a tool for specifying, refining and developing systems in a mathematical and rigorous, but simple, way. Services are specified using the B method and the feature interaction problem is modelled as a violation of invariant properties. The B method is supported by software that helps the specifier of services and features. We have not only modelled services within the B technology, but we have also extended the B methodology with a novel way of combining abstract machines.

A Methodology to Solve Optimisation Problems with MAS Application to the Graph Colouring Problem

Developing multi-agent systems may be a rather difficult task. Having confidence in the result is still more difficult. In this article, we describe a methodology that helps in this task. This methodology is dedicated to global optimization problems that can be solved combining local constraints. We developed CASE tools to support this methodology which are also presented. Finally, we show how this methodology has been successfully used to develop a multi-agent system for the graph colouring problem.

Service specifications: to B, or not to B

The paper introduces a new use for the B method as a means of specifying telecommunication services with the help of abstract machines and, consequently, it defines a formal framework for studying the feature interaction problem. An interaction is defined as a violation of an invariant and is detected when combining two or more abstract machines. The current B method is extended to allow the composition of abstract machines. The B method is supported by sofware that helps the specifier of services and features. We have not only modelled services within the B technology, but we have also extended the possibilities of B through the composition of abstract machines.

SPACE: A method to increase tracability in MAS development

This paper deals with a method and a model called SPACE allowing to design multiagent systems. Their main interest is to introduce tools to design and to validate the produced system at the same time. First, the main steps of the proposed method are described. Then, the different components of the SPACE model are defined. Finally, two case studies (on a BDI model and on a graph colouring problem) show how the method and the model can be applied.

Specifying and verifying holonic agents with GDT4MAS

This paper describes how specific holonic multi-agent systems can be specified and how their correctness can be proven with an extended version of the GDT4MAS model. This model allows the specification of multi-agent systems and the verification of their correctness with theorem proving techniques. Introducing holonic agents in this model allows the enhancement of its expressiveness. Moreover, the proof system associated to this model can be easily extended in order to prove the correctness of multi-agent systems using such agents. The paper first describes the initial GDT4MAS model. Then the need for some kinds of holonic agents and their proposed specification based on specific decomposition operators are presented. It is followed by a focus on how the proof system can be adapted to prove the correctness of the behaviour of these new agents. Last but not least, all these proposals are illustrated on a case study.

A Dynamic Clustering Algorithm for Mobile Objects

In this paper, a multiagent algorithm for dynamic clustering is presented. This kind of clustering is intended to manage mobile data and so, to be able to continuously adapt the built clusters. First of all, potential applications of this algorithm are presented. Then the specific constraints for this kind of clustering are studied. A multiagent architecture satisfying these constraints is described. It combines an ants algorithm with a cluster agents layer which are executed simultaneously. Finally, the first experimental results of our work are presented.

A New Proof System to Verify GDT Agents

The GDT4MAS model is dedicated to the formal specification of agents and multiagents systems. It has been presented in previous articles [7, 6]. The proof mechanism relies on proof schemas that generate proof obligations, that is to say first-order formulae that can be proven (in most cases) by an automatic prover (such as PVS). In this article, we present a new version of proof schemas that increase the number of proofs that can be performed.

Variant Extensions to Prove MAS Behaviours

In this article, it is shown how the behaviour of a multi-agent system can be validated thanks to proof. At first, the method used is briefly presented [10]. Then, the variant notion is presented and an extension of this notion to prove MAS is introduced. In the third part, the proof technique is illustrated for the prey-predator problem: the behaviour of the predators can be induced from the failures in the proof process.