We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
This paper empirically investigates the use and behaviour of Evolution Strategies (ES) algorithms on problems such as function optimisation and the use of evolutionary artificial ...
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
We present a novel method for automatically acquiring strategies for the double auction by combining evolutionary optimization together with a principled game-theoretic analysis. ...