Learning Control for Xpilot Agents in the Core

Xpilot, a network game where agents engage in space combat, has been shown to be a good test bed for controller learning systems. In this paper, we introduce the Core, an Xpilot learning environment where a population of learning agents interact locally through tournament selection, crossover, and mutation to produce offspring in the evolution of controllers. The system does not require the researcher to develop a fitness function or suitable agents to engage with the evolving agent. Instead, it employs a form of co-evolution where the environment, made up of the population of agents, evolves to continually challenge individual agents evolving within it. Tests show its successful use in evolving controllers for combat agents in Xpilot.