Evolution of Neural Networks to Play the Game of Dots-and-Boxes

dc.creatorWeaver, Lex
dc.creatorBossomaier, Terry
dc.date1998-09-28
dc.date.accessioned2026-07-07T03:23:41Z
dc.date.available2026-07-07T03:23:41Z
dc.descriptionDots-and-Boxes is a child's game which remains analytically unsolved. We implement and evolve artificial neural networks to play this game, evaluating them against simple heuristic players. Our networks do not evaluate or predict the final outcome of the game, but rather recommend moves at each stage. Superior generalisation of play by co-evolved populations is found, and a comparison made with networks trained by back-propagation using simple heuristics as an oracle.
dc.description8 pages, 5 figures, LaTeX 2.09 (works with LaTeX2e)
dc.identifierhttps://arxiv.org/abs/cs/9809111
dc.identifierhttp://arxiv.org/abs/cs/9809111
dc.identifierAlife V: Poster Presentations, May 16-18 1996, pages 43-50
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/33039
dc.subjectNeural and Evolutionary Computing
dc.subjectMachine Learning
dc.subjectI.2.6
dc.titleEvolution of Neural Networks to Play the Game of Dots-and-Boxes
dc.typetext

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