Méta-analyse pour le génie logiciel des systèmes multi-agents

Abstract : From a general point of view this thesis addresses an automatic path to build a solution choosing a compatible set of building blocks to provide such a solution to solve a given problem. To create the solution it is considered the compatibility of each available building block with the problem and also the compatibility between each building block to be employed within a solution all together. In the particular perspective of this thesis the building blocks are meta-models and the given problem is a description of a problem that can be solved using software using a multi-agent system paradigm. The core of the thesis proposal is the creation of a process based on a multi-agent system itself. Such a process analyzes the given problem and the available meta-models then it matches both and thus it suggests one possible solution (based on meta-models) for the problem. Nevertheless if no solution is found it also indicates that the problem can not be solved through this paradigm using the available meta-models. The process addressed by the thesis consists of the following main steps: (1) Through a process of characterization the problem description is analyzed in order to locate the solution domain and therefore employ it to choose a list of most domain compatible meta-models as candidates. (2) There are required also meta-model characterization that evaluate each meta-model performance within each considered domain of solution. (3) The matching step is built over a multi-agent system where each agent represents a candidate meta-model. Within this multi-agent system each agent interact with each other in order to find a group of suitable meta-models to represent a solution. Each agent use as criteria the compatibility between their represented candidate meta-model with the other represented meta-models. When a group is found the overall compatibility with the given problem is evaluated. Finally each agent has a solution group. Then these groups are compared between them in order to find the most suitable to solve the problem and then to decide the final group. This thesis focuses on providing a process and a prototype tool to solve the last step. Therefore the proposed path has been created using several concepts from meta-analysis, cooperative artificial intelligence, Bayesian cognition, uncertainty, probability and statistics.
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Luis Alfonso Razo Ruvalcaba. Méta-analyse pour le génie logiciel des systèmes multi-agents. Intelligence artificielle [cs.AI]. Université de Grenoble, 2012. Français. ⟨NNT : 2012GRENM107⟩. ⟨tel-01547236⟩

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