Neuro-cognitive Model of Move Location in The Game of Go

Terence Bossomaier; Jason Traish; Fernand Gobet; Peter CR Lane

doi:10.1109/IJCNN.2012.6252377

Neuro-cognitive Model of Move Location in The Game of Go

Terence Bossomaier, Jason Traish, Fernand Gobet, Peter CR Lane

Research output: Book chapter/Published conference paper › Conference paper › peer-review

9 Citations (Scopus)

Abstract

Although computer Go players are now better than humans on small board sizes, they are still a fair way from the top human players on standard board sizes. Thus the nature of human expertise is of great interest to artificial intelligence. Human play relies much more on pattern memory and has been extensively explored in chess. The big challenge in Go is local-global interaction - local search is good but global integration is weak. We used techniques based on the cognitive neuroscience of chess to predict optimal areas to move using perceptual chunks, which we cross-validated against game records comprising upwards of five million positions. Prediction to within a small window was about 50%, a remarkable result.

Original language	English
Title of host publication	Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN)
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-7
Number of pages	7
ISBN (Electronic)	9781467314909
DOIs	https://doi.org/10.1109/IJCNN.2012.6252377
Publication status	Published - 2012
Event	IEEE International Joint Conference on Neural Networks: IJCNN 2012 - Brisbane Convention Centre, Brisbane, Australia Duration: 10 Jun 2012 → 15 Jun 2012 https://web.archive.org/web/20120510232940/http://www.ieee-wcci2012.org/ (Conference website)

Conference

Conference	IEEE International Joint Conference on Neural Networks
Country/Territory	Australia
City	Brisbane
Period	10/06/12 → 15/06/12
Other	The 2012 IEEE World Congress on Computational Intelligence (IEEE WCCI 2012) is the largest technical event in the field of computational intelligence. It will host three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012). IEEE WCCI 2012 will be held in Brisbane, a awe-inspiring city situated along the Brisbane River and the eastern coast line of Australia. The congress will provide a stimulating forum for scientists, engineers, educators, and students from all over the world to discuss and present their research findings on computational intelligence.
Internet address	https://web.archive.org/web/20120510232940/http://www.ieee-wcci2012.org/ (Conference website)

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10.1109/IJCNN.2012.6252377

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title = "Neuro-cognitive Model of Move Location in The Game of Go",

abstract = "Although computer Go players are now better than humans on small board sizes, they are still a fair way from the top human players on standard board sizes. Thus the nature of human expertise is of great interest to artificial intelligence. Human play relies much more on pattern memory and has been extensively explored in chess. The big challenge in Go is local-global interaction - local search is good but global integration is weak. We used techniques based on the cognitive neuroscience of chess to predict optimal areas to move using perceptual chunks, which we cross-validated against game records comprising upwards of five million positions. Prediction to within a small window was about 50%, a remarkable result.",

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author = "Terence Bossomaier and Jason Traish and Fernand Gobet and Lane, {Peter CR}",

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year = "2012",

doi = "10.1109/IJCNN.2012.6252377",

language = "English",

pages = "1--7",

booktitle = "Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

url = "https://web.archive.org/web/20120510232940/http://www.ieee-wcci2012.org/",

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Bossomaier, T, Traish, J, Gobet, F & Lane, PCR 2012, Neuro-cognitive Model of Move Location in The Game of Go. in Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN). IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 1-7, IEEE International Joint Conference on Neural Networks, Brisbane, Queensland, Australia, 10/06/12. https://doi.org/10.1109/IJCNN.2012.6252377

Neuro-cognitive Model of Move Location in The Game of Go. / Bossomaier, Terence; Traish, Jason; Gobet, Fernand et al.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN). United States: IEEE, Institute of Electrical and Electronics Engineers, 2012. p. 1-7.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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AB - Although computer Go players are now better than humans on small board sizes, they are still a fair way from the top human players on standard board sizes. Thus the nature of human expertise is of great interest to artificial intelligence. Human play relies much more on pattern memory and has been extensively explored in chess. The big challenge in Go is local-global interaction - local search is good but global integration is weak. We used techniques based on the cognitive neuroscience of chess to predict optimal areas to move using perceptual chunks, which we cross-validated against game records comprising upwards of five million positions. Prediction to within a small window was about 50%, a remarkable result.

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KW - Computational modeling

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KW - Electronic mail

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Neuro-cognitive Model of Move Location in The Game of Go

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