Coalition formation based on a task-oriented collaborative ability vector

Coalition formation based on a task-oriented collaborative ability vector
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基于任务导向的协作能力向量的联盟形成

DOI:
10.1631/fitee.1601608
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发表时间:
2017-02
影响因子:
3
通讯作者:
Wen-jie CHEN
Wen-jie CHEN
中科院分区:
工程技术3区
文献类型:
--
作者:
Hao FANG;Shao-lei LU;Jie CHEN;Wen-jie CHEN

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联盟形成是多智能体系统中的一个重要的协调问题,而对智能体的协作能力进行正确的描述是处理这一问题的基本和关键前提。本文建立了面向任务的协同能力模型,将面向任务的五种能力提取出来,形成协同能力向量。还描述了任务需求向量。此外,为了减少过度竞争,提出了一种具有随机机制的联盟形成方法。提出了一种人工智能算法来补偿预期任务需求和实际任务需求之间的差异,从而提高了智能体对人类命令的认知能力。仿真结果表明了该模型和分布式人工智能算法的有效性。
Coalition formation is an important coordination problem in multi-agent systems, and a proper description of collaborative abilities for agents is the basic and key precondition in handling this problem. In this paper, a model of task-oriented collaborative abilities is established, where five task-oriented abilities are extracted to form a collaborative ability vector. A task demand vector is also described. In addition, a method of coalition formation with stochastic mechanism is proposed to reduce excessive competitions. An artificial intelligent algorithm is proposed to compensate for the difference between the expected and actual task requirements, which could improve the cognitive capabilities of agents for human commands. Simulations show the effectiveness of the proposed model and the distributed artificial intelligent algorithm.
DOI: 10.1287/inte.24.6.19
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