Improving Game AI Design Using Adversarial Agents

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


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.


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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