Expert prediction, symbolic learning, and neural networks an experiment on greyhound racing

Hsinchun Chen, Peter Buntin Rinde, Linlin She, Siunie Sutjahjo, Chris Sommer, Daryl Neely

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Uncertainty, an inevitable problem in problem solving can be reduced by seeking the advice of an expert in terms of computer algorithms such as machine learning. Machine learning encompasses different types of solutions. In the present investigation, a different problem-solving scenario called game playing is investigated. For this purpose, greyhound racing, a complex domain that involves almost 50 performance variables for eight competing dogs in a race is considered. For every race, each dog's past history is complete and freely available to bettors. This article discusses the experimental procedures as well as the results obtained in the process.

Original languageEnglish (US)
Pages (from-to)6
Number of pages1
JournalIEEE expert
Volume9
Issue number6
StatePublished - Dec 1 1994

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Chen, H., Rinde, P. B., She, L., Sutjahjo, S., Sommer, C., & Neely, D. (1994). Expert prediction, symbolic learning, and neural networks an experiment on greyhound racing. IEEE expert, 9(6), 6.