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Integrated task and motion planning has emerged as a challenging problem in sequential decision making, where a robot needs to compute high-level strategy and low-level motion plans for solving complex tasks.
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Towards a unified theory of state abstraction for mdps
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Concise finite-domain representations for pddl planning tasks
Malte Helmert · 2009
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Practical solution techniques for first-order MDPs
Scott Sanner and Craig Boutilier · 2009
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Automated Construction of Robotic Manipulation Programs
Rosen Diankov · 2010
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Sampling-based motion and symbolic action planning with geometric and differential constraints
E. Plaku and G. D. Hager · 2010
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Relational dynamic influence diagram language (rddl): Language description
Scott Sanner · 2010
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Combining high-level causal reasoning with low-level geometric reasoning and motion planning for robotic manipulation
Esra Erdem, Kadir Haspalamutgil, Can Palaz, Volkan Patoglu, and Tansel Uras · 2011
Integrated task and motion planning in belief space
Leslie Pack Kaelbling and Tomás Lozano-Pérez · 2013
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State aggregation in monte carlo tree search
Jesse Hostetler, Alan Fern, and Tom Dietterich · 2014
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A modular approach to task and motion planning with an extensible planner-independent interface layer
Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, and Pieter Abbeel · 2014
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FFrob: An efficient heuristic for task and motion planning
Caelan Reed Garrett, Tomás Lozano-Pérez, and Leslie Pack Kaelbling · 2015
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Modular task and motion planning in belief space
Dylan Hadfield-Menell, Edward Groshev, Rohan Chitnis, and Pieter Abbeel · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Hierarchical task and motion planning in the now
Leslie Pack Kaelbling and Tomás Lozano-Pérez · 2011
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Heuristic search for generalized stochastic shortest path mdps
A Kolobov, Mausam, DS Weld, and H Geffner · 2011
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Planning with semantic attachments: An object-oriented view
Andreas Hertle, Christian Dornhege, Thomas Keller, and Bernhard Nebel · 2012
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Accounting for uncertainty in simultaneous task and motion planning using task motion multigraphs
Ioan A Şucan and Lydia E Kavraki · 2012
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Research priorities for robust and beneficial artificial intelligence
Stuart Russell, Daniel Dewey, and Max Tegmark · 2015
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Markovian state and action abstractions for MDPs via hierarchical MCTS
Aijun Bai, Siddharth Srivastava, and Stuart J Russell · 2016
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Incremental task and motion planning: A constraint-based approach
Neil T Dantam, Zachary K Kingston, Swarat Chaudhuri, and Lydia E Kavraki · 2016
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Deep reinforcement learning in parameterized action space
Matthew Hausknecht and Peter Stone · 2016
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