2022/09/01 by Nathan Partlan, Luis Antonio Cruz Soto, Partlan, Nathan +9 · 1 citation
Computer Science · Mathematics · Social Sciences · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #Artificial intelligence #Biology #Computer science #Context (archaeology) #D.2.2 #Digital Games and Media #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Game design #Game engine #Game play #Genetic programming #Human-Computer Interaction (cs.HC) #Human–computer interaction #I.2.1 #Mathematics #Neural and Evolutionary Computing (cs.NE) #Tree (set theory)
paper · pdf · doi:10.48550/arxiv.2209.01020
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2022/09/01 · openalex created_date 2022/09/06 · openalex updated_date 2026/07/28
To assist game developers in crafting game NPCs, we present EvolvingBehavior, a novel tool for genetic programming to evolve behavior trees in Unreal Engine 4. In an initial evaluation, we compare evolved behavior to hand-crafted trees designed by our researchers, and to randomly-grown trees, in a 3D survival game. We find that EvolvingBehavior is capable of producing behavior approaching the designer's goals in this context. Finally, we discuss implications and future avenues of exploration for co-creative game AI design tools, as well as challenges and difficulties in behavior tree evolution.