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Authors: Evelyn Conceição Santos Batista 1 ; Wouter Caarls 1 ; Leonardo A. Forero 2 and Marco Aurélio C. Pacheco 1

Affiliations: 1 Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil ; 2 Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, Brazil

Keyword(s): Autonomous Agent, Transfer Learning, Reinforcement Learning, Deep Learning, Vizdoom, DQN.

Abstract: This paper consists of a study on deep learning by visual reinforcement for autonomous robots through transfer learning techniques. The simulation environments tested in this study are realistic environments where the challenge of the robot was to learn and transfer knowledge in different contexts, taking advantage of the experience of previous environments in future environments. This type of approach, besides adding knowledge to autonomous robots, reduces the number of training epochs for the algorithm even in complex environments, justifying the use of transfer learning techniques.

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Paper citation in several formats:
Batista, E.; Caarls, W.; Forero, L. and Pacheco, M. (2021). Training an Agent to Find and Reach an Object in Different Environments using Visual Reinforcement Learning and Transfer Learning. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 732-741. DOI: 10.5220/0010236807320741

@conference{icaart21,
author={Evelyn Concei\c{C}ão Santos Batista. and Wouter Caarls. and Leonardo A. Forero. and Marco Aurélio C. Pacheco.},
title={Training an Agent to Find and Reach an Object in Different Environments using Visual Reinforcement Learning and Transfer Learning},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={732-741},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010236807320741},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Training an Agent to Find and Reach an Object in Different Environments using Visual Reinforcement Learning and Transfer Learning
SN - 978-989-758-484-8
IS - 2184-433X
AU - Batista, E.
AU - Caarls, W.
AU - Forero, L.
AU - Pacheco, M.
PY - 2021
SP - 732
EP - 741
DO - 10.5220/0010236807320741
PB - SciTePress

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