Combining evolutionary algorithms and case-based reasoning for learning high-quality shooting strategies in AI birds

Abstract

Self-adaptation and the ability to assimilate new knowledge are two fundamental characteristics of intelligent systems. In this paper we leverage methods from evolutionary optimization and from case-based reasoning to construct an agent that is able to evolve in such a way that it is able to successfully master the popular video game Angry Birds.