2 citations · 2 across the 3 of their papers we have counts for
4 papers
Gym-RTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning
Shengyi Huang, Santiago Ontañón, Chris Bamford +1
In recent years, researchers have achieved great success in applying Deep Reinforcement Learning (DRL) algorithms to Real-time Strategy (RTS) games, creating strong autonomous agen…
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…
Neural Game Engine: Accurate learning of generalizable forward models from pixels
Chris Bamford, Simon Lucas
Access to a fast and easily copied forward model of a game is essential for model-based reinforcement learning and for algorithms such as Monte Carlo tree search, and is also benef…
A Local Approach to Forward Model Learning: Results on the Game of Life Game
Simon M. Lucas, Alexander Dockhorn, Vanessa Volz +6
This paper investigates the effect of learning a forward model on the performance of a statistical forward planning agent. We transform Conway's Game of Life simulation into a sing…