4 citations · 6 across the 3 of their papers we have counts for
4 papers
Atari-5: Distilling the Arcade Learning Environment down to Five Games
Matthew Aitchison, Penny Sweetser, Marcus Hutter
The Arcade Learning Environment (ALE) has become an essential benchmark for assessing the performance of reinforcement learning algorithms. However, the computational cost of gener…
Learning to Deceive in Multi-Agent Hidden Role Games
Matthew Aitchison, Lyndon Benke, Penny Sweetser
Deception is prevalent in human social settings. However, studies into the effect of deception on reinforcement learning algorithms have been limited to simplistic settings, restri…
DNA: Proximal Policy Optimization with a Dual Network Architecture
Matthew Aitchison, Penny Sweetser
This paper explores the problem of simultaneously learning a value function and policy in deep actor-critic reinforcement learning models. We find that the common practice of learn…
Optimal Use of Experience in First Person Shooter Environments
Matthew Aitchison
Although reinforcement learning has made great strides recently, a continuing limitation is that it requires an extremely high number of interactions with the environment. In this…