Probabilistic neural network playing a simple game

0411134 - UTIA-B 20030121 RIV IT eng C - Conference Paper (international conference)
Grim, Jiří - Somol, Petr - Pudil, Pavel - Just, P.
Probabilistic neural network playing a simple game.
Florence: University of Florence, 2003. In: Artificial Neural Networks in Pattern Recognition. Proceedings. - (Marinai, S.; Gori, M.), s. 132-138
[IAPR TC3 Workshop 2003 /1./. Florence (IT), 12.09.2003-13.09.2003]
R&D Projects: GA ČR GA402/01/0981; GA ČR GA402/03/1310; GA AV ČR KSK1019101
Institutional research plan: CEZ:AV0Z1075907
Keywords : probabilistic neural networks * finite mixtures * EM algorithm
Subject RIV: BB - Applied Statistics, Operational Research

The goal of the paper is to design a probabilistic neural network playing a simple two-player game "Tic-Tac-Toe". The game is considered as a problem of a repeating evaluation of preferences of possible moves. Assuming the probabilistic neural network in the role of the evaluation function we can solve the problem by estimating the probability distribution of advantageous moves. The unknown distribution is estimated in the form of a finite discrete mixture of product components by means of EM algorithm.
Permanent Link: http://hdl.handle.net/11104/0131221