Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies
Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies
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DOI：
10.1016/j.ins.2007.09.024
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发表时间：
2008-02
期刊：
影响因子：
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通讯作者：
K. T. Seow;K. Sim
中科院分区：
文献类型：
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作者：
K. T. Seow;K. Sim
本文提出了一种分布式智能体模型，该模型应用信念-愿望-意图(BDI)推理和协商来协同解决线性分配问题(LAP)。在资源分配中，LAP被认为是寻求为每个任务同时分配一个不同的资源，以优化线性和目标函数。该模型为分布式环境中的有效资源分配提供了基于代理的基础。对基于BDI协商模型的分布式代理算法进行了理论分析和实验验证。为了提高平均协商速度和解的质量，采用了两种初始化启发式算法和两种不同的推理控制策略，后者产生了基本算法的不同变体。大量的模拟表明，在某种特定意义上，所有的启发式算法组合都能在足够短的时间内产生接近最优解。并对研究工作的意义和适用性进行了讨论。
In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.