Novel information processing techniques are being actively explored to overcome
fundamental limitations associated with CMOS scaling. A new paradigm of adaptive …

This paper surveys research on applying neuroevolution (NE) to games. In neuroevolution,
artificial neural networks are trained through evolutionary algorithms, taking inspiration from …

In evolutionary computation, the fitness function normally measures progress toward an
objective in the search space, effectively acting as an objective function. Through deception …

Coevolutionary algorithms approach problems for which no function for evaluating potential
solutions is present or known. Instead, algorithms rely on the aggregation of outcomes from …

Novelty search is a recent artificial evolution technique that challenges traditional
evolutionary approaches. In novelty search, solutions are rewarded based on their novelty …

This paper presents COVNET, a new cooperative coevolutionary model for evolving artificial
neural networks. This model is based on the idea of coevolving subnetworks that must …

An evolutionary algorithm has taught itself how to play the game of checkers without using
features that would normally require human expertise. Using only the raw positions of pieces …

Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …

In order to promote computer Go and stimulate further development and research in the
field, the event activities, Computational Intelligence Forum and World 9 \,*\, 9 Computer Go …

Mathematical games provide a framework for studying intelligent behavior in models of real-
world settings or restricted domains. The obstacle comes in choosing the appropriate …