Tomoyuki Kaneko

DEIR: Efficient and Robust Exploration through Discriminative-Model-Based Episodic Intrinsic Rewards

Exploration is a fundamental aspect of reinforcement learning (RL), and its effectiveness is a deciding factor in the performance of RL algorithms, especially when facing sparse extrinsic rewards. Recent studies have shown the effectiveness of encouraging exploration with intrinsic rewards estimated…