CFP2: Autonomous Agent Learning

The submission site is still open.

Autonomous Agent Learning Special Session for the 2011 IEEE Congress on Evolutionary Computation (CEC 2011)

An autonomous agent has a self-sufficient control program that allows it to operate in its environment. A pre-programmed controller, although it may yield the desired results, is laborious to develop and does not provide a means for adaptations necessitated by changes in agent capability or the environment. Learning control through some form of evolutionary computation can save development time and allow the same control system to adapt to different environments, and in some cases, adapt to changes in the agent=92s capabilities and environment.

Two areas where autonomous agents are of significant importance are in robotics and interactive video games. Autonomous robots are used for tasks that are too dangerous or impractical for humans to perform. These include exploration in dangerous or remote locations, intelligence gathering, and office or domestic assistance. Agents in interactive video games are used to provide additional players (team members or opponents) to interact with human players. Many of these games are used purely for entertainment, but include games used for training. In either case, having competitive, human like autonomous agents in a game increases the realism and entertainment value. In both autonomous robots and interactive video game agents, learning systems can be significant aspects of their development and enhancement.

This special session aims to discuss autonomous agent learning systems with the primary emphasis on the use of evolutionary computation or reinforcement learning to learn control programs for autonomous robots and interactive video game agents. Topics for contributions include, but may not be limited to the use of reinforcement learning or the varying forms of evolutionary computation to learn controllers for robots, simulations of robots, interactive video game agents, teams of agents, and predator/prey agents.

Special session organizers: Gary Parker, Connecticut College, USA ( snipped-for-privacy@conncoll.edu) Hisashi Handa, Okayama University, Japan ( snipped-for-privacy@sdc.it.okayama- u.ac.jp) Lee Graham, Connecticut College, USA ( snipped-for-privacy@conncoll.edu)

The submission site is still open:

any of the organizers if you have any questions.