Asymmetric distributed constrained optimization method for multi-Agent system

Abstract

The invention provides an asymmetric distributed constrained optimization method for a multi-Agent system. The method includes the following steps that a controller receives Agent information and obtains an asymmetric relation and an Agent connected graph is established; according to the connecting relation between nodes in the Agent connected graph, a chain structure based on the sequence is established; depth-first trees are established for the Agent connected graph in a depth-first mode; through a branch and bound strategy, weighted values of root nodes of different depth-first trees are calculated and finally an optimal tree structure is obtained; depending on the obtained optimal tree structure, Agent behavior parameters in the multi-Agent system are adjusted. According to the asymmetric characteristic of the multi-Agent system, a prediction mechanism is introduced, the defects of incomplete information decision making are overcome, an Agent can estimate the influences of behaviors of the Agent, the more effective strategy is obtained, the non-monotone characteristic of gains is changed to a certain degree, and the balance between individual benefits and overall benefits is achieved.

Description

technical field [0001] The invention relates to an asymmetric distributed constraint optimization method, in particular to an asymmetric distributed constraint optimization method for a multi-agent system. Background technique [0002] The multi-agent system is the study of how to coordinate their knowledge, goals, skills and mutual planning among a group of autonomous agents to take action or solve problems. The system has been gradually applied in practical applications such as task scheduling, resource allocation, sensor network, traffic management, and microgrid configuration. However, in these application fields, the "symmetry" feature is still used for multi-agent systems, that is, the characteristics, value (strategy) space and cost (income) function of each agent to other agents that have a constraint relationship with it are still used. With accurate information, each Agent has no personal preference information and privacy, which simplifies the process of solving ...

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Problems solved by technology

[0004] In order to overcome the defects existing in the above-mentioned prior art, the purpose of the present invention is to provide a multi-Agent system asymmetric distributed constraint optimization method to solve the problems of the response of Agent asymmetric incomplete information, two-way cost solution and the privacy of individual revenue Combination problems and how to design Agent organizational structure and strategies and make them better match problems

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