An Approach for Fault Tolerance in Multi-Agent Systems using Learning Agents

An Approach for Fault Tolerance in Multi-Agent Systems using Learning Agents

Mounira Bouzahzah, Ramdane Maamri
Copyright: © 2015 |Pages: 15
DOI: 10.4018/IJIIT.2015070103
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Abstract

Through this paper, the authors propose a new approach to get fault tolerant multi-agent systems using learning agents. Generally, the exceptions in the multi-agent system are divided into two main groups: private exceptions that are treated directly by the agents and global exceptions that combine all unexpected exceptions that need handlers to be solved. The proposed approach solves the problem of these global exceptions using learning agents. This work uses a formal model called hierarchical plans to model the activities of the system's agents in order to facilitate the exception detection and to model the communication with the learning agent. This latter uses a modified version of the Q Learning Algorithm in order to choose which handler can be used to solve an exceptions. The paper tries to give a new direction in the field of fault tolerance in multi-agent systems by using learning agents, the proposed solution makes it possible to adapt the handler used in case of failure within the context changes and treat repeated exceptions using learning agent experiences.
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The multi agent system is defined as system composed of agents situated in some environment and interacted according to certain relations. Multi agent systems are used largely when dealing within applications that need decentralization and cooperation. Unfortunately, these systems are prone to failures of different sources. Researchers in field of fault tolerance propose many solutions to get robust multi agent systems. Exception handling represents one of the solutions used to assure fault tolerance, it solves exceptions that occur during the system execution. This technique is proposed, in reality for distributed and concurrent systems but it is, later, used for multi agent systems.

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