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http://dx.doi.org/10.14372/IEMEK.2020.15.5.261

Pacman Game Reinforcement Learning Using Artificial Neural-network and Genetic Algorithm  

Park, Jin-Soo (Korea National University of Transportation(KNUT))
Lee, Ho-Jeong (Korea National University of Transportation(KNUT))
Hwang, Doo-Yeon (Korea National University of Transportation(KNUT))
Cho, Soosun (Korea National University of Transportation(KNUT))
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.15, no.5, 2020 , pp. 261-268 More about this Journal
Abstract
Genetic algorithms find the optimal solution by mimicking the evolution of natural organisms. In this study, the genetic algorithm was used to enable Pac-Man's reinforcement learning, and a simulator to observe the evolutionary process was implemented. The purpose of this paper is to reinforce the learning of the Pacman AI of the simulator, and utilize genetic algorithm and artificial neural network as the method. In particular, by building a low-power artificial neural network and applying it to a genetic algorithm, it was intended to increase the possibility of implementation in a low-power embedded system.
Keywords
Reinforcement learning; Artificial neural network; Genetic algorithm; Pacman game; Simulator;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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