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Abstract: One of the persistent themes in Artificial Life research is the use of co-evolutionary arms races in the development of specific and complex behaviors. However, other than Sims's work on artificial robots, most of the work has attacked very simple games of prisoners dilemma or predator and prey. Following Tesauro's work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of the dice, application of... (Update)
Context of citations to this paper: More
.... by embedding the learner in a learning environment which responds to its own improvements in a never ending spiral (Pollack) [9]. Moriarty gives a survey into general learning with evolutionary algorithms [8] In 2000, Chellapilla and Fogel successfully developed...
.... Rather than enter a progressive arms race, competing populations may stabilise into a suboptimal equilibrium, or mediocre stable state [3, 7, 8, 6]. As individuals are only rewarded for out performing their contemporary oponents, it is possible for earlier adaptations to be...
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BibTeX entry: (Update)
J. Pollack, A. Blair, and M. Land. Coevolution of a Backgammon Player. In Proceedings of the Fifth Artificial Life Conference, Nara, Japan, 1996. http://citeseer.ist.psu.edu/pollack96coevolution.html More
@inproceedings{ pollack97coevolution,
author = "Jordan B. Pollack and Alan D. Blair and Mark Land",
title = "Coevolution of a Backgammon Player",
booktitle = "Artificial {L}ife {V}: {P}roc.\ of the {F}ifth {I}nt.\ Workshop on the {S}ynthesis and {S}imulation of {L}iving {S}ystems",
publisher = "The MIT Press",
address = "Cambridge, MA",
editor = "Christopher G. Langton and Katsunori Shimohara",
pages = "92--98",
year = "1997",
url = "citeseer.ist.psu.edu/pollack96coevolution.html" }
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