Self-Adaptive Aided Decision-Making using a Multi-Agent System
نویسندگان
چکیده
Information required for decision-making in complex applications, such as flood forecast or maritime surveillance, can be represented using a mathematical function. However, due to the complexity of the considered applications and their dynamics, the parameters involved in the mathematical function can be hard to value a priori. This paper first introduces the mathematical function representing decision-making situation. It then presents a Multi-Agent System, called PaMAS (Parameter Multi-Agent System) that is able to learn values of the parameters involved in the considered situation, on the fly, autonomously, cooperatively and by self-adaptation. More precisely, it defines the behaviour of PaMAS agents and their learning strategy by self-adaptation of parameters values.
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تاریخ انتشار 2015