Wee Sun Lee

Contrastive Variational Model-Based Reinforcement Learning for Complex Observations.

2020 · arXiv (Cornell University)

Deep model-based reinforcement learning (MBRL) has achieved great sample-efficiency and generalization in decision making for sophisticated simulated tasks, such as Atari games. However, real-world robot decision making requires reasoning with complex natural visual observations. This …

Context-Hierarchy Inverse Reinforcement Learning

2022 · arXiv (Cornell University)

An inverse reinforcement learning (IRL) agent learns to act intelligently by observing expert demonstrations and learning the expert's underlying reward function. Although learning the reward functions from demonstrations has achieved great success in various tasks, …