The Swarm Intelligence in Games website was launched today. The site aims to become the primary on-line source for information on the study of swarm intelligence applied to the games domain.

Games are defined in broad terms to include:

• Board and card games.
• Economic and mathematical games.
• Imperfect information and non-deterministic games.
• Predator/Prey games.
• Console and more realistic simulation games.

Some of the research focuses on:

• Learning and adaptation in games.
• Knowledge-free and self-learning in games.
• Theoretical and empirical analysis of swarm intelligence algorithms and representations for games.
• Multi-agent and multi-strategy learning.

From a swarm intelligence perspective, the key algorithms involved in conducting the games research are:

• Ant Colony Optimization.
• Particle Swarm Optimization.
• Swarm-based Neural Networks.
• Swarm-based Coevolution.