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

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).