Razvan Pascanu

We propose MASP, a meta-learned similarity-based regularization for RL with macro-actions. MASP improves exploration, credit assignment, and transfer across tasks, outperforming Rainbow DQN in challenging benchmarks.

We provide a formal definition of plasticity under minimal assumptions, and highlight a fundamental connection to empowerment