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Authors: Degang Wu and Kwok Yip Szeto

Affiliation: The Hong Kong University of Science and Technology, Hong Kong

ISBN: 978-989-758-052-9

Keyword(s): Genetic Algorithm, Parrondo Game, Optimization, Game Theory.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Evolutionary Computing ; Game Theory Applications ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: Parrondo game, which introduction is inspired by the flashing Brownian ratchet, presents an apparently paradoxical situation at it shows that there are ways to combine two losing games into a winning one. The original Parrondo game consists of two individual games, game A and game B. Game A is a slightly losing coin-tossing game. Game B has two coins, with an integer parameter $M$. If the current cumulative capital (in discrete unit) is a multiple of $M$, an unfavorable coin $p_b$ is used, otherwise a favorable $p_g$ coin is used. Game B is also a losing game if played alone. Paradoxically, combination of game A and game B could lead to a winning game, either through random mixture, or deterministic switching. In deterministic switching, one plays according to a sequence such as ABABB. Exhaustive search and backward induction have been applied to the search for optimal finite game sequence. In this paper, we apply genetic algorithm (GA) to search for optimal game sequences with a give n length $N$ for large $N$. Based on results obtained through a problem-independent GA, we adapt the point mutation operator and one-point crossover operator to exploit the structure of the optimal game sequences. We show by numerical results the adapted problem-dependent GA has great improvement in performance. (More)

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Paper citation in several formats:
Wu D. and Szeto K. (2014). Applications of Genetic Algorithm on Optimal Sequence for Parrondo Games.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014) ISBN 978-989-758-052-9, pages 30-37. DOI: 10.5220/0005070400300037

@conference{ecta14,
author={Degang Wu and Kwok Yip Szeto},
title={Applications of Genetic Algorithm on Optimal Sequence for Parrondo Games},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)},
year={2014},
pages={30-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005070400300037},
isbn={978-989-758-052-9},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)
TI - Applications of Genetic Algorithm on Optimal Sequence for Parrondo Games
SN - 978-989-758-052-9
AU - Wu D.
AU - Szeto K.
PY - 2014
SP - 30
EP - 37
DO - 10.5220/0005070400300037

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