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Planning

3112 directly classified papers

Papers per year

Papers

Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies ALT 2020
Planning Paths Through Unknown Space by Imagining What Lies Therein CORL 2020
Learning an Expert Skill-Space for Replanning Dynamic Quadruped Locomotion over Obstacles CORL 2020
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects CORL 2020
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning NIPS 2020
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation NIPS 2020
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs NIPS 2020
Task-Completion Dialogue Policy Learning via Monte Carlo Tree Search with Dueling Network EMNLP 2020
Untangling Dense Knots by Learning Task-Relevant Keypoints CORL 2020
Stein Variational Model Predictive Control CORL 2020
Learning Stability Certificates from Data CORL 2020
Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations CORL 2020
Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations CORL 2020
BayesRace: Learning to race autonomously using prior experience CORL 2020
Reactive motion planning with probabilisticsafety guarantees CORL 2020
Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled Intersections CORL 2020
TCP ≈ RDMA: CPU-efficient Remote Storage Access with i10 NSDI 2020
Learning 3D Dynamic Scene Representations for Robot Manipulation CORL 2020
Compositional Generalization by Learning Analytical Expressions NIPS 2020
Belief-Dependent Macro-Action Discovery in POMDPs using the Value of Information NIPS 2020
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning NIPS 2020
Reinforced Molecular Optimization with Neighborhood-Controlled Grammars NIPS 2020
Learning Compositional Neural Programs with Recursive Tree Search and Planning NIPS 2019
Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text IJCNLP 2019
When to Trust Your Model: Model-Based Policy Optimization NIPS 2019