reinforcement learning

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.

Control What You Can: Intrinsically Motivated Task-Planning Agent

The Control What You Can (CWYC) method learns to control components of the environment to achieve multi-step goals by combining task planning with surprise and learning progress based intrinsic motivation.

Embodied Multimodal Multitask Learning

Proposes multitask model to jointly learn semantic goal navigation and embodied question answering.

Automatic Goal Generation for Reinforcement Learning Agents

Applies curriculum learning to a RL context to achieve policies.