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Authors: Jurij Chizhov and Arkady Borisov

Affiliation: Riga Technical University, Latvia

ISBN: 978-989-8111-66-1

Keyword(s): Reinforcement learning, Non-Markovian deterministic environments, Intelligent agents, Agent control.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Autonomous Systems ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems ; Uncertainty in AI

Abstract: This paper considers the problem of intelligent agent functioning in non-Markovian environments. We advice to divide the problem into two subproblems: just finding non-Markovian states in the environment and building an internal representation of original environment by the agent. The internal representation is free from non Markovian states because insufficient number of additional dynamically created states and transitions are provided. Then, the obtained environment might be used in classical reinforcement learning algorithms (like SARSA(λ)) which guarantee the convergence by Bellman equation. A great difficulty is to recognize different “copies” of the same states. The paper contains a theoretical introduction, ideas and problem description, and, finally, an illustration of results and conclusions.

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Paper citation in several formats:
Chizhov J.; Borisov A. and (2009). APPLYING Q-LEARNING TO NON-MARKOVIAN ENVIRONMENTS.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 306-311. DOI: 10.5220/0001755603060311

@conference{icaart09,
author={Jurij Chizhov and Arkady Borisov},
title={APPLYING Q-LEARNING TO NON-MARKOVIAN ENVIRONMENTS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={306-311},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001755603060311},
isbn={978-989-8111-66-1},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - APPLYING Q-LEARNING TO NON-MARKOVIAN ENVIRONMENTS
SN - 978-989-8111-66-1
AU - Chizhov, J.
AU - Borisov, A.
PY - 2009
SP - 306
EP - 311
DO - 10.5220/0001755603060311

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