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Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging

机译:人工资本市场在多机器人觅食任务分配中的应用

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摘要

Because of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.
机译:由于多智能体系统的高速,高效,鲁棒性和灵活性,近年来,对这些系统的技术越来越感兴趣。人工市场机制是多代理系统中众所周知的协商多代理协议之一。本文介绍了人工资本市场作为一种市场机制的新变种,并将其应用于多机器人觅食问题。在这个人造的资本市场中,机器人将通过对某些资产的投资而受益,这些资产被定义为执行觅食任务。每项投资都有成本和结果。投资者有限的初始资金限制了他们的投资。提出了协商协议以用于代理的决策。定性分析揭示了收敛速度,接近最优解和算法的鲁棒性。数值分析表明,相对于四个先前开发的启发式算法,该方法在四个性能标准方面具有优势。

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