Molecule Builder: Environment for Testing Reinforcement Learning Agents

Petr Hyner; Petr Hyner; Jan Hůla; Jan Hůla; Mikoláš Janota

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Paper

Molecule Builder: Environment for Testing Reinforcement Learning Agents

Topics: Bio-inspired models and solutions; Learning Paradigms and Algorithms; Reinforcement Learning

In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA, 450-458, 2023 , Rome, Italy

Authors: Petr Hyner ^{1

;

2} ; Jan Hůla ^{2

;

3} and Mikoláš Janota ³

Affiliations: ¹ Department of Informatics and Computers, Faculty of Science, University of Ostrava, Ostrava, Czech Republic ; ² Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Ostrava, Czech Republic ; ³ Czech Technical University in Prague, Prague, Czech Republic

Keyword(s): Reinforcement Learning, Subgoals, Environment, Agent.

Abstract: We present a reinforcement learning environment designed to test agents’ ability to solve problems that can be naturally decomposed using subgoals. This environment is built on top of the PyVGDL game engine and enables to generate problem instances by specifying the dependency structure of subgoals. Its purpose is to enable faster development of Reinforcement Learning algorithms that solve problems by proposing subgoals and then reaching these subgoals.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Hyner, P.; Hůla, J. and Janota, M. (2023). Molecule Builder: Environment for Testing Reinforcement Learning Agents. In Proceedings of the 15th International Joint Conference on Computational Intelligence - NCTA; ISBN 978-989-758-674-3; ISSN 2184-3236, SciTePress, pages 450-458. DOI: 10.5220/0012257900003595

@conference{ncta23,
author={Petr Hyner. and Jan Hůla. and Mikoláš Janota.},
title={Molecule Builder: Environment for Testing Reinforcement Learning Agents},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - NCTA},
year={2023},
pages={450-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012257900003595},
isbn={978-989-758-674-3},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - NCTA
TI - Molecule Builder: Environment for Testing Reinforcement Learning Agents
SN - 978-989-758-674-3
IS - 2184-3236
AU - Hyner, P.
AU - Hůla, J.
AU - Janota, M.
PY - 2023
SP - 450
EP - 458
DO - 10.5220/0012257900003595
PB - SciTePress