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Authors: Jan Teichmann ; Eduardo Alonso and Mark Broom

Affiliation: City University London, United Kingdom

ISBN: 978-989-758-157-1

Keyword(s): Darwinian Fitness, Reward, Prey-predator Co-evolution.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Life ; Co-Evolution and Collective Behavior ; Computational Intelligence ; Evolution Strategies ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: In this paper we present a model that, based on the principle of total energy balance (similar to energy conservation in Physics), bridges the gap between Darwinian fitness theories and reward-driven theories of behaviour. Results show that it is possible to accommodate the reward maximization principle underlying modern approaches in behavioural reinforcement learning and traditional fitness approaches. Our framework, presented within a prey-predator model, may have important consequences in the study of behaviour.

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Paper citation in several formats:
Teichmann, J.; Alonso, E. and Broom, M. (2015). A Reward-driven Model of Darwinian Fitness.In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 174-179. DOI: 10.5220/0005591501740179

@conference{ecta15,
author={Jan Teichmann. and Eduardo Alonso. and Mark Broom.},
title={A Reward-driven Model of Darwinian Fitness},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={174-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005591501740179},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - A Reward-driven Model of Darwinian Fitness
SN - 978-989-758-157-1
AU - Teichmann, J.
AU - Alonso, E.
AU - Broom, M.
PY - 2015
SP - 174
EP - 179
DO - 10.5220/0005591501740179

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