Evolving reactive NPCs for the real-time simulation game
Jin-Hyuk Hong, Sung‐Bae Cho · 2005
Abstract- AI in computer games has been highlighted in recent, but manual works for designing the AI cost a great deal. An evolutionary algorithm has developed strategies without using features that are based on the developer. Since the real-time reactive selection of behaviors for NPCs is required for better playing, a reactive behavior system consisting neural networks is presented. Using only the raw information on games, the evolutionary algorithm optimizes the reactive behavior system based on a co-evolutionary method. For demonstration of the proposed method, we have developed a real-time simulation game called ‘Build & Build’. As the results, we have obtained emergent and interesting behaviors that are adaptive to the environment, and confirmed the applicability of evolutionary approach to designing NPCs ’ behaviors without relying on human expertise. 1