Continuous On-line Evolution of Agent Behaviours with Cartesian Genetic Programming
This addresses the need for adaptive agent behaviors in multi-agent systems, but it appears incremental as it builds on existing evolutionary computation approaches.
The paper tackles the problem of continuous on-line adaptation of agent behaviors using evolutionary algorithms, presenting a method that searches for behavioral policies to cope with the environment, but no concrete results or numbers are provided.
Evolutionary Computation has been successfully used to synthesise controllers for embodied agents and multi-agent systems in general. Notwithstanding this, continuous on-line adaptation by the means of evolutionary algorithms is still under-explored, especially outside the evolutionary robotics domain. In this paper, we present an on-line evolutionary programming algorithm that searches in the agent design space for the appropriate behavioural policies to cope with the underlying environment. We discuss the current problems of continuous agent adaptation, present our on-line evolution testbed for evolutionary simulation.