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Work control in balanced DRC systems supported by negotiation procedures between autonomous agents

机译:自治代理之间的协商程序支持平衡DRC系统中的工作控制

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In a Multi Agent System (i.e., MAS) several decision agents, with an internal knowledge and reasoning engine, can negotiate for resources and assignment by exchanging register messages based on communication rules. The interaction mechanism between agents, sharing common transmission channels, can be modelled as a cooperative payoff process using a game-negotiation approach. This study proposed an autonomous agents control architecture where negotiation among agents competes for optimal performances while choosing work control rules in unbalanced system. It is applied in a real Dual-Resource Constrained system. The model includes evaluation of design (i.e., Workforce and Distance and Buffer Capacity) and sensitivity (i.e., operator variability in terms of cycle time coefficient of Variation) factors to assign work load strategies (i.e., control When-rule and Where-rule) to workers based on negotiation between competing performances (in terms of System-Effects and Human-Effects).
机译:在多代理系统(即,MAS)中,具有内部知识和推理引擎的几个决策代理可以通过基于通信规则交换注册消息来协商资源和分配。可以使用游戏协商方法将共享公共传输渠道的代理之间的交互机制建模为协作收益过程。这项研究提出了一种自主的代理人控制架构,其中代理人之间的协商会在选择不平衡系统中的工作控制规则时竞争最佳性能。它应用于实际的双重资源约束系统中。该模型包括对设计(即劳动力,距离和缓冲能力)和灵敏度(即操作员根据周期时间变异系数的可变性)因素进行评估,以分配工作负荷策略(即控制何时规则和何处规则)根据竞争绩效之间的协商(根据系统效果和人为效果)向员工提供。

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