Key Technologies of Confrontational Intelligent Decision Support for Multi-Agent Systems |
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Authors: | Yun Zhang |
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Affiliation: | 1.School of Computer Science and Technology,Xi’ an University of Science and Technology,Xi’an, Shaanxi,P.R. China |
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Abstract: | This paper firstly studies intelligent learning techniques based on reinforcement learning theory. It proposes an improved multi-agent cooperative learning method that can be shared through continuous learning and the strategies of individual agents to achieve the integration of multi-agent strategy and learning in order to improve the capabilities of intelligent multi-agent systems. Secondly, according to the analysis of data mining and AHP theory, a new concept is proposed to build a data mining model (based on intelligent learning) that has been named ‘ACMC’ (AHP Construct Mining Component); designed ACMC strategy evaluation and assistant decision-making based on multiagent systems, to achieve a strategic assessment of the current situation and reach a final decision. Finally, after research on Intelligent Decision Technology based on game theory, aspects of game theory are employed to deal with the real demand of confrontational environments. |
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