Playing Tic-Tac-Toe Using a Modified Neural Network and an Improved Genetic Algorithm
This paper presents an algorithm of playing game tic-tac-toe. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (GA). In the proposed NN, the neuron has two activation transfer functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. It will be shown that the proposed NN and GA provide a better performance than that by the traditional approach
Year of publication: |
2018
|
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Authors: | Lam, H.K. |
Other Persons: | Ling, S.H. (contributor) ; Leung, F.H.F. (contributor) ; Tam, P.K.S. (contributor) |
Publisher: |
[2018]: [S.l.] : SSRN |
Subject: | Evolutionärer Algorithmus | Evolutionary algorithm | Neuronale Netze | Neural networks | Theorie | Theory |
Saved in:
freely available
Extent: | 1 Online-Ressource (13 p) |
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Series: | Computer Science Preprint Archive ; Vol. 2002, Issue 8, pp 811-823 |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 2002 erstellt |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012927292
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