Abstract
In multi-agent systems, agents should socially cooperate with their neighboring agents in order to solve task allocation problem in open and dynamic network environments. This paper proposes an agent-based architecture to handle different tasks; in particular, we focus on planning and distributed task allocation. In the proposed approach, each agent uses the fuzzy logic technique to select the alternative plans. We also propose an efficient task allocation algorithm that takes into consideration agent architectures and allows neighboring agents to help to perform a task as well as the indirectly related agents in the system. We illustrate our line of thought with a Benchmark Production System used as a running example in order to explain better our contribution. A set of experiments was conducted to demonstrate the efficiency of our planning approach and the performance of our distributed task allocation method.
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