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Application of Multi-Agent Reinforcement Learning Techniques in Sequential Games

Authors:
Vanya Markova
Ventseslav Shopov

Keywords: autonomous agents; deep reinforcement learning; multi-agent systems; collective behaviour

Abstract:
This article focuses on the application of multi-agent deep reinforcement learning techniques in sequential games. The main hypothesis is that deep reinforcement learning and collective behaviour approach demonstrate better performance than classic reinforcement learning. So autonomous agents are capable of discovering good solutions to the problem at hand by cooperate with other learners.

Pages: 42 to 47

Copyright: Copyright (c) IARIA, 2018

Publication date: May 20, 2018

Published in: conference

ISSN: 2308-3913

ISBN: 978-1-61208-634-7

Location: Nice, France

Dates: from May 20, 2018 to May 24, 2018