Adaptive Graph Planning Protocol: An Adaption Approach to Collaboration in Open Multi-agent Systems
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The adaptive system requires each agent to provide effective adaptive scheme in runtime according to dynamic changes in the environment. This paper offers an Adaptive Graph Planning Protocol (AGPP) that uses the Goal-Capability-Commitment (GCC) meta-model to dynamically reconstruct. The method uses the concept of capability to represent the executable capabilities possessed by the Agent, and introduces the concept of context state to represent the dynamic environment in the adaptive system. The adaptive graph planning protocol generation method is optimized by calculating the semantic matching degree of the context state. To evaluate the effectiveness of our approach, we provide an experimental scheme based on intelligent robot parking system (IRPS). This scheme verifies the execution time efficiency of this method and the adaptive efficiency of offline in case of emergency.
KeywordsOpen multi-agent system Graph planning Adaptive collaboration Goal-Capability-Commitment model
Project supported by the National Natural Science Foundation of China under Grant (No. 61502355), supported by Scientific Research Project of Education Department of Hubei Province (No. Q20181508), supported by Graduate Innovative Fund of Wuhan Institute of Technology (No. CX2018203).
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