Snake game AI: Movement rating functions and evolutionary algorithm-based optimization

Jia Fong Yeh; Pei Hsiu Su; Shi Heng Huang; Tsung-Che Chiang

doi:10.1109/TAAI.2016.7880166

Snake game AI: Movement rating functions and evolutionary algorithm-based optimization

Jia Fong Yeh, Pei Hsiu Su, Shi Heng Huang, Tsung-Che Chiang

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Snake game is a computer action game, whose goal is to control a snake to move and collect food in a map. In this paper we develop a controller based on movement rating functions considering smoothness, space, and food. Scores given by these functions are aggregated by linear weighted sum, and the snake takes the action that leads to the highest score. To find a set of good weight values, we apply an evolutionary algorithm. We examine several algorithm variants of different crossover and environmental selection operators. Experimental results show that our design method is able to generate smart controllers.

Original language	English
Title of host publication	TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	256-261
Number of pages	6
ISBN (Electronic)	9781509057320
DOIs	https://doi.org/10.1109/TAAI.2016.7880166
Publication status	Published - 2017 Mar 16
Event	2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 - Hsinchu, Taiwan Duration: 2016 Nov 25 → 2016 Nov 27

Other

Other	2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016
Country/Territory	Taiwan
City	Hsinchu
Period	2016/11/25 → 2016/11/27

Keywords

artificial intelligence (AI)
evolutionary algorithm
game
snake

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Control and Optimization
Information Systems

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10.1109/TAAI.2016.7880166

Cite this

Yeh, J. F., Su, P. H., Huang, S. H., & Chiang, T-C. (2017). Snake game AI: Movement rating functions and evolutionary algorithm-based optimization. In TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings (pp. 256-261). [7880166] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAAI.2016.7880166

Snake game AI : Movement rating functions and evolutionary algorithm-based optimization. / Yeh, Jia Fong; Su, Pei Hsiu; Huang, Shi Heng; Chiang, Tsung-Che.

TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 256-261 7880166.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yeh, JF, Su, PH, Huang, SH & Chiang, T-C 2017, Snake game AI: Movement rating functions and evolutionary algorithm-based optimization. in TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings., 7880166, Institute of Electrical and Electronics Engineers Inc., pp. 256-261, 2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016, Hsinchu, Taiwan, 2016/11/25. https://doi.org/10.1109/TAAI.2016.7880166

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abstract = "Snake game is a computer action game, whose goal is to control a snake to move and collect food in a map. In this paper we develop a controller based on movement rating functions considering smoothness, space, and food. Scores given by these functions are aggregated by linear weighted sum, and the snake takes the action that leads to the highest score. To find a set of good weight values, we apply an evolutionary algorithm. We examine several algorithm variants of different crossover and environmental selection operators. Experimental results show that our design method is able to generate smart controllers.",

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doi = "10.1109/TAAI.2016.7880166",

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AB - Snake game is a computer action game, whose goal is to control a snake to move and collect food in a map. In this paper we develop a controller based on movement rating functions considering smoothness, space, and food. Scores given by these functions are aggregated by linear weighted sum, and the snake takes the action that leads to the highest score. To find a set of good weight values, we apply an evolutionary algorithm. We examine several algorithm variants of different crossover and environmental selection operators. Experimental results show that our design method is able to generate smart controllers.

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Snake game AI: Movement rating functions and evolutionary algorithm-based optimization

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