多智能体搜索与任务分配问题中的信息共享

Mathias Minos-Stensrud, H. Moen, Jan Dyre Bjerknes
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引用次数: 0

摘要

在多智能体系统背景下,信息共享对广义组合搜索和任务分配问题的影响尚未得到详细的研究。在此基础上,从通信距离和信息容错性两个方面对一种简单的群体智能机制——呼出机制和一种基本的博弈论拍卖机制进行了比较和分析。仿真结果表明,该拍卖机制在不同通信距离下表现良好,但在通信距离较低和面对错误信息时存在问题。然而,呼出机制在通信距离较低和代理之间的信息传递不确定时表现得更好。此外,对于间歇性通信距离,呼出执行几乎等同于拍卖,但由于大通信距离的“过度协调”的固有属性,代理在解决任务时变得“过度承诺”,而牺牲了搜索新任务的代价。这种基本的系统行为只能在搜索和任务分配的组合问题中研究,
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Information sharing in multi-agent search and task allocation problems
The impact of information sharing in the generalized problem of combined search and task allocation has not been studied in detail in the context of multi-agent systems. Thus, a simple swarm intelligence mechanism called call-out and a basic game theoretic auction mechanism are compared and analyzed in terms of communication distance and information fault tolerance. Simulations show that the auction mechanism performs well under varying communication distances but has problems when the communication distance is low and when facing faulty information. The call-out mechanism, however, performs significantly better when communication distances are low and when information transfer between agents is uncertain. Furthermore, call-out performs almost equal to auction for intermittent communication distances but due to the inherent property of “over-coordination” for large communication distances agents become “over-committed” in solving tasks at the expense of searching for new tasks. This fundamental system behavior can only be studied in the combined search and task allocation problem,
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