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Found 6 papers, 4 papers with code
PG3: Policy-Guided Planning for Generalized Policy Generation
In this work, we study generalized policy search-based methods with a focus on the score function used to guide the search over policies.
Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances
We present a strategy for designing and building very general robot manipulation systems involving the integration of a general-purpose task-and-motion planner with engineered and learned perception modules that estimate properties and affordances of unknown objects.
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks
We conclude that learning to predict a sufficient set of objects for a planning problem is a simple, powerful, and general mechanism for planning in large instances.
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation.
Flexible and Efficient Long-Range Planning Through Curious Exploration
In contrast, deep reinforcement learning (DRL) methods use flexible neural-network-based function approximators to discover policies that generalize naturally to unseen circumstances.
