Deep learning has triggered the current rise of artificial intelligence and is the workhorse of
today's machine intelligence. Numerous success stories have rapidly spread all over …

Procedural content generation (PCG) refers to the practice of generating game content, such
as levels, quests or characters, algorithmically. Motivated by the need to make games …

Autonomous agents have made great strides in specialist domains like Atari games and Go.
However, they typically learn tabula rasa in isolated environments with limited and manually …

The study of zero-shot generalisation (ZSG) in deep Reinforcement Learning (RL) aims to
produce RL algorithms whose policies generalise well to novel unseen situations at …

Abstract We introduce Procgen Benchmark, a suite of 16 procedurally generated game-like
environments designed to benchmark both sample efficiency and generalization in …

Training generally-capable agents with reinforcement learning (RL) remains a significant
challenge. A promising avenue for improving the robustness of RL agents is through the use …

The availability of challenging benchmarks has played a key role in the recent progress of
machine learning. In cooperative multi-agent reinforcement learning, the StarCraft Multi …

Recent advances in artificial intelligence have been driven by the presence of increasingly
realistic and complex simulated environments. However, many of the existing environments …

Foundation models have shown impressive adaptation and scalability in supervised and self-
supervised learning problems, but so far these successes have not fully translated to …

To make deliberate progress towards more intelligent and more human-like artificial
systems, we need to be following an appropriate feedback signal: we need to be able to …