34 citations · 94 across the 29 of their papers we have counts for
43 papers
Joint action loss for proximal policy optimization
Xiulei Song, Yizhao Jin, Greg Slabaugh +1
PPO (Proximal Policy Optimization) is a state-of-the-art policy gradient algorithm that has been successfully applied to complex computer games such as Dota 2 and Honor of Kings. I…
Visualising Multiplayer Game Spaces
James Goodman, Diego Perez-Liebana, Simon Lucas
We compare four different `game-spaces' in terms of their usefulness in characterising multi-player tabletop games, with a particular interest in any underlying change to a game's…
Predictive Control Using Learned State Space Models via Rolling Horizon Evolution
Alvaro Ovalle, Simon M. Lucas
A large part of the interest in model-based reinforcement learning derives from the potential utility to acquire a forward model capable of strategic long term decision making. Ass…
Rinascimento: searching the behaviour space of Splendor
Ivan Bravi, Simon Lucas
The use of Artificial Intelligence (AI) for play-testing is still on the sidelines of main applications of AI in games compared to performance-oriented game-playing. One of the mai…
Griddly: A platform for AI research in games
Chris Bamford, Shengyi Huang, Simon Lucas
In recent years, there have been immense breakthroughs in Game AI research, particularly with Reinforcement Learning (RL). Despite their success, the underlying games are usually i…
AI and Wargaming
James Goodman, Sebastian Risi, Simon Lucas
Recent progress in Game AI has demonstrated that given enough data from human gameplay, or experience gained via simulations, machines can rival or surpass the most skilled human p…