Laszlo Szoke

Adaptive Curriculum Learning With Successor Features for Imbalanced Compositional Reward Functions

This work addresses the challenge of reinforcement learning with reward functions that feature highly imbalanced components in terms of importance and scale. Reinforcement learning algorithms generally struggle to handle such imbalanced reward functions effectively. Consequently, they often converge