George Long

Queen Mary University of London

George is an iGGi PhD student interested in AI assisted game design, specifically the process of game balancing. After graduating with a BSc in Computer Science at the University of Essex, he joined iGGi in 2021.

His research focuses on how AI can be used to balance games, in particular games with asymmetric elements. He has most recently been working on using agentic Large Language Models to theorycraft optimal strategies in games.

A description of George's research:

"My research focuses on balancing games through identifying overpowered or unfair rules, which can then be accounted for:

My previous work identified how we can estimate unit point costs in miniature wargames. These wargames are played by forming armies comprised of units, the sum of each unit's point costs must be within the total army budget. Therefore it is crucial that these point costs accurately represent how useful the unit is in combat. We used Linear Regression and Linear Programming to estimate these point costs and improve the balance of an example game.

Currently, I am investigating how we can use Large Language Models to theorycraft optimal strategies in games.I used an agentic approach where an agent comes up with an initial theory, tests in out in games, and uses the results of the game to create an iterative feedback loop to improve the strategy."