UC Berkeley

Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

Region Proposal Interaction Networks (RPIN) learn to reason about object trajectories in a latent region-proposal feature space, that captures object and contextual information.

Entity Abstraction in Visual Model-Based Reinforcement Learning

The Object-centric perception, prediction, and planning (OP3) framework demonstrates strong generalization to novel configurations in block stacking tasks by symmetrically processing entity representations extracted from raw visual observations.

Automatic Goal Generation for Reinforcement Learning Agents

Applies curriculum learning to a RL context to achieve policies.