Quantifying generalization in reinforcement learning

1. 1Use CoinRun to train and evaluate reinforcement learning agents
2. 2Analyze the results to understand how well the agents generalize to novel situations
3. 3Compare the performance of different algorithms and techniques in CoinRun
4. 4Apply the insights gained from CoinRun to improve the generalization of agents in other environments

ML researchers and engineers on a team can benefit from CoinRun to evaluate and improve their agents' ability to generalize, and this can inform product managers and software engineers on the team about the potential applications and limitations of reinforcement learning

💡 CoinRun provides a metric for an agent's ability to transfer its experience to novel situations

🤖 CoinRun: a new environment to test reinforcement learning generalization!