Effects of Communication in Cooperative Q-Learning

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Darbyshire, Paul and Wang, D (2010) Effects of Communication in Cooperative Q-Learning. International Journal of Innovative Computing, Information and Control, 6 (5). pp. 2113-2126. ISSN 1349-4198


Reinforcement learning has been utilized to investigate the distributed learn- ing problem in many different multi-agent and team-based scenarios. Invariably, using a distributed learning approach by allowing agents to exchange what they have learned, by either direct communication or by episodic exchanges, the team does better in terms of achieving its goals. The cause-effect relationship between communication and improved performance has been studied in a number of different team based scenarios; however, it is difficult to find a detailed analysis of the effect the communication has as a function of time on the elements of the simulation. Of particular interest is the effect on the learning of agents when part of a communicating multi-agent system. Studies show the effects of cooperative learning in the form of accelerated group learning rates; but it is difficult to pinpoint 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 function of time on a multi-agent simulation based on a military distillation, utilizing a modified Q-learning algorithm.

Item type Article
URI https://vuir.vu.edu.au/id/eprint/7339
Subjects Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems
Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > SEO Classification > 970108 Expanding Knowledge in the Information and Computing Sciences
Keywords ResPubID21439, ResPubID20955. agent communication, reinforcement learning, multi-agent systems, complex system, learning rates, knowledge landscape
Citations in Scopus 4 - View on Scopus
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