Monte-Carlo evaluation consists in estimating a position by averaging the outcome of several random continuations, and can serve as an evaluation function at the leaves of a min-ma...
We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing a...
We are developing a new problem-solving methodology based on a self-organization paradigm. To realize our future goal of self-organizing computational systems, we have to study co...
This paper discusses a practical framework for the semi automatic construction of evaluation functions for games. Based on a structured evaluation function representation, a proced...
Abstract. Designing an adequate fitness function requiressubstantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human ...
This paper introduces a new evaluation function, called δ, for the Bandwidth Minimization Problem for Graphs (BMPG). Compared with the classical β evaluation function used, our ...
Eduardo Rodriguez-Tello, Jin-Kao Hao, Jose Torres-...
A general technique is proposed to deal with the formalization of intuition and human-oriented concepts in competition thinking games like chess, such as defensive play, attack, t...
Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. In the game of Lines of Action (LOA), which has been dominated in the past by αβ, M...
This paper proposes an automated web site evaluation approach using machine learning to cope with ranking problems. Evaluating web sites is a significant task for web service beca...