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Authors: Johannes Nauta ; Yara Khaluf and Pieter Simoens

Affiliation: Department of Information Technology, Ghent University, Ghent and Belgium

Keyword(s): Brownian Motion, Exploration, Ornstein-Uhlenbeck Process.

Abstract: In model-based Reinforcement Learning, an agent aims to learn a transition model between attainable states. Since the agent initially has zero knowledge of the transition model, it needs to resort to random exploration in order to learn the model. In this work, we demonstrate how the Ornstein-Uhlenbeck process can be used as a sampling scheme to generate exploratory Brownian motion in the absence of a transition model. Whereas current approaches rely on knowledge of the transition model to generate the steps of Brownian motion, the Ornstein-Uhlenbeck process does not. Additionally, the Ornstein-Uhlenbeck process naturally includes a drift term originating from a potential function. We show that this potential can be controlled by the agent itself, and allows executing non-equilibrium behavior such as ballistic motion or local trapping.

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Paper citation in several formats:
Nauta, J., Khaluf, Y. and Simoens, P. (2019). Using the Ornstein-Uhlenbeck Process for Random Exploration. In Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS; ISBN 978-989-758-366-7; ISSN 2184-5034, SciTePress, pages 59-66. DOI: 10.5220/0007724500590066

@conference{complexis19,
author={Johannes Nauta and Yara Khaluf and Pieter Simoens},
title={Using the Ornstein-Uhlenbeck Process for Random Exploration},
booktitle={Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS},
year={2019},
pages={59-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007724500590066},
isbn={978-989-758-366-7},
issn={2184-5034},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS
TI - Using the Ornstein-Uhlenbeck Process for Random Exploration
SN - 978-989-758-366-7
IS - 2184-5034
AU - Nauta, J.
AU - Khaluf, Y.
AU - Simoens, P.
PY - 2019
SP - 59
EP - 66
DO - 10.5220/0007724500590066
PB - SciTePress

- Science and Technology Publications, Lda.
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