Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning

Understand

We present AIRS: Automatic Intrinsic Reward Shaping that intelligently and adaptively provides high-quality intrinsic rewards to enhance exploration in reinforcement learning (RL).

• More specifically, AIRS selects shaping function from a predefined set based on the estimated task return in real-time, providing reliable exploration incentives and alleviating the biased objective problem.
• Moreover, we develop an intrinsic reward toolkit to provide efficient and reliable implementations of diverse intrinsic reward approaches.
• We test AIRS on various tasks of MiniGrid, Procgen, and DeepMind Control Suite.