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Expert Prediction, Symbolic Learning, and Neural Networks: An Experiment on Greyhound Racing

Chen, Hsinchun and Buntin, P. and She, Linlin and Sutjahjo, S. and Sommer, C. and Neely, D. (1994) Expert Prediction, Symbolic Learning, and Neural Networks: An Experiment on Greyhound Racing. IEEE Expert 9(6):pp. 21-27.

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Abstract

For our research, we investigated a different problem-solving scenario called game playing, which is unstructured, complex, and seldom-studied. We considered several real-life game-playing scenarios and decided on greyhound racing. The large amount of historical information involved in the search poses a challenge for both human experts and machine-learning algorithms. The questions then become: Can machine-learning techniques reduce the uncertainty in a complex game-playing scenario? Can these methods outperform human experts in prediction? Our research sought to answer these questions.

EPrint Type:Journal Article (Paginated)
Keywords:National Science Digital Library, NSDL, Artificial Intelligence Lab, AI Lab, Machine-learning algorithms
Subjects:Artificial Intelligence
ID Code:504
Deposited On:13 October 2004
Alternative Locations:http://ai.bpa.arizona.edu/go/papers.html
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