Evolving multi-modal behavior in NPCs

This is an Accepted Manuscript of an article published by IEEE. Schrum, J., & Miikkulainen, R. (2009). Evolving multi-modal behavior in NPCs. In 2009 IEEE Symposium on Computational Intelligence and Games (pp. 325–332). https://doi.org/10.1109/CIG.2009.5286459. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")

Schrum, Jacob

Miikkulainen, Risto

2016-12-13

2016-12-13

2009

Schrum, J., & Miikkulainen, R. (2009). Evolving multi-modal behavior in NPCs. In 2009 IEEE Symposium on Computational Intelligence and Games (pp. 325–332). https://doi.org/10.1109/CIG.2009.5286459

https://collections.southwestern.edu/s/suscholar/item/227

Evolution is often successful in generating complex behaviors, but evolving agents that exhibit distinctly different modes of behavior under different circumstances (multi-modal behavior) is both difficult and time consuming. This paper presents a method for encouraging the evolution of multi-modal behavior in agents controlled by artificial neural networks: A network mutation is introduced that adds enough output nodes to the network to create a new output mode. Each output mode completely defines the behavior of the network, but only one mode is chosen at any one time, based on the output values of preference nodes. With such structure, networks are able to produce appropriate outputs for several modes of behavior simultaneously, and arbitrate between them using preference nodes. This mutation makes it easier to discover interesting multi-modal behaviors in the course of neuroevolution.

English

IEEE

Artificial neural networks

Software agents

Computer games

Non-player characters

Multi-modal behavior

Neuroevolution

Article