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- W114927286 abstract "Reinforcement learning has been utilized to investigate the distributed learn-ing problem in many different multi-agent and team-based scenarios. Invariably, using adistributed learning approach by allowing agents to exchange what they have learned, byeither direct communication or by episodic exchanges, the team does better in terms ofachieving its goals. The cause-effect relationship between communication and improvedperformance has been studied in a number of different team based scenarios; however, itis difficult to find a detailed analysis of the effect the communication has as a function oftime on the elements of the simulation. Of particular interest is the effect on the learningof agents when part of a communicating multi-agent system. Studies show the effects ofcooperative learning in the form of accelerated group learning rates; but it is difficult topinpoint through the literature exactly how this observed effect is realized within individ-ual agents over time. This paper investigates the effect of communication as a functionof time on a multi-agent simulation based on a military distillation, utilizing a modifiedQ-learning algorithm." @default.
- W114927286 created "2016-06-24" @default.
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- W114927286 date "2010-01-01" @default.
- W114927286 modified "2023-09-28" @default.
- W114927286 title "Effects of Communication in Cooperative Q-Learning" @default.
- W114927286 hasPublicationYear "2010" @default.
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