Analyzing Approaches to Extending and Implementing Behavior Trees in Computer Games

With the development of the computer game industry, it is too hard for traditional methods, like finite state machines and behavior trees, to drive intelligent non-player characters behaviors, especially under complex environments.This paper explores and analyzes three methods - an event driven approach to behavior trees, simulating human-like emotions in behavior trees, and integrating machine learning in behaviour trees and allowing them to evolve themselves through genetic programming. This review synthesizes the findings from existing studies, highlighting the potential of these extensions to significantly enhance player immersion and the authenticity of gaming experiences.