In this paper, we investigate several neural network architectures using co-evolutionary learning techniques, with the objective to learn to play Othello ...
In this paper, we investigate several neural network architectures using co-evolutionary learning techniques, with the objective to learn to play Othello ...
ABSTRACT. Othello has long been a favorite AI subject due to its very simple rules, its very low branching factor, its well defined strategic.
Evolutionary computation was used to train neural networks to learn the play the game of Othello. Each neural network represents a strategy based on board ...
Our approach was to evolve a population of neural networks in the game of Othello. ... The networks consisted of three layers (input, output, and one hidden layer).
Missing: Multi- | Show results with:Multi-
People also ask
What is the best algorithm for Othello?
What are multilayer neural networks?
What is ann in ml?
What is the difference between single layer and multilayer neural networks?
Fig. 1 Model of the neural-network-based evaluation function. The model is based on a feed-forward MLP, consisting of a 64 x 1 vector input (Othello board ...
Evolving Multi-Layer Neural Networks for Othello ... Othello has long been a favorite AI subject due to its very simple rules, its very low branching factor, its ...
In this paper we describe an Othello program, BILL, that has far surpassed the generation of Othello programs represented by IAGO. Its performance is due to ...
Abstract This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then ...
Nov 17, 2017 · Here we ask whether CNNs have a practical potential for games of a small branching factor and much smaller board size, for which the minimax- ...