James Goodman

James Goodman is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. He teaches the postgraduate module Artificial Intelligence in Games, focusing on AI techniques applied to game design and analysis. His research explores the intersection of artificial intelligence and gaming, particularly in tabletop games, reinforcement learning, and game balancing. He has contributed to frameworks such as PyTAG and investigates topics like skill assessment, randomness measurement, and multi-agent systems in game environments.

Research interests include applying AI to board games and real-time strategy games, analyzing game mechanics, and developing algorithms for game optimization. His work bridges theoretical AI advancements with practical applications in gaming, emphasizing both academic and industrial relevance.

James has published extensively on game AI, with recent focus on reinforcement learning challenges in tabletop games and opponent modeling in real-time strategy games. His studies also address game autobalancing and the role of stochasticity in gameplay.

Awards: None explicitly mentioned in the provided text.

Advising and Grants: No specific advisees or grant details are listed here. His contributions primarily revolve around teaching and research publications.

Labs/Teams: While not detailed in the text, his affiliation with the School of Electronic Engineering and Computer Science likely involves collaboration with research groups focused on AI and game development within the institution.