Constructing Complex NPC Behavior via Multi-Objective Neuroevolution

12 years 3 days ago
Constructing Complex NPC Behavior via Multi-Objective Neuroevolution
It is difficult to discover effective behavior for NPCs automatically. For instance, evolutionary methods can learn sophisticated behaviors based on a single objective, but realistic game playing requires different behaviors at different times. Such complex behavior is difficult to achieve. What is needed are multi-objective methods that reward different behaviors separately, and allow them to be combined to produce multi-modal behavior. While such methods exist, they have not yet been applied to generating multi-modal behavior for NPCs. This paper presents such an application: In a domain with noisy evaluations and contradictory fitness objectives, evolution based on a scalar fitness function is inferior to multi-objective optimization. The multi-objective approach produces agents that excel at the task and develop complex, interesting behaviors.
Jacob Schrum, Risto Miikkulainen
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Authors Jacob Schrum, Risto Miikkulainen
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