Improving Game AI Design Using Adversarial Agents

Lead Research Organisation: Queen Mary, University of London
Department Name: Sch of Electronic Eng & Computer Science

Abstract

This project proposes a novel method for improving the quality of behaviour of human authored agents by pitting them against trained agents and observing what bad behaviours/exploits the trained agents reveal. Authored agents refer to AI agents whose actions are explicitly designed by programmers using traditional techniques such as Utility functions, Behaviour Trees and state machines; trained agents refer to agents whose behaviour is learned by playing many games against the authored agents.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S51570X/1 01/10/2018 30/09/2022
2309406 Studentship EP/S51570X/1 24/09/2018 30/09/2023 Nathan Michael John-McDougall