Abstract
Our objective is to devise learning algorithms that an autonomous learning agent can use while functioning in a multiagent environment. In order to achieve this objective, we pose the learning problem as a Reinforcement Learning problem in a multiagent environment. Keeping in line with past research, we use the canonical game theoretic framework of repeated matrix games as our chosen multiagent environment.
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© 2014 Springer International Publishing Switzerland
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Chakraborty, D. (2014). Background. In: Sample Efficient Multiagent Learning in the Presence of Markovian Agents. Studies in Computational Intelligence, vol 523. Springer, Cham. https://doi.org/10.1007/978-3-319-02606-0_2
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DOI: https://doi.org/10.1007/978-3-319-02606-0_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02605-3
Online ISBN: 978-3-319-02606-0
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