CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agents

Understand

Progress in continual reinforcement learning has been limited due to several barriers to entry: missing code, high compute requirements, and a lack of suitable benchmarks.

• In this work, we present CORA, a platform for Continual Reinforcement Learning Agents that provides benchmarks, baselines, and metrics in a single code package.
• The benchmarks we provide are designed to evaluate different aspects of the continual RL challenge, such as catastrophic forgetting, plasticity, ability to generalize, and sample-efficient learning.
• Three of the benchmarks utilize video game environments (Atari, Procgen, NetHack).