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In recent years, researchers have made significant progress in devising reinforcement-learning algorithms for optimizing linear temporal logic (LTL) objectives and LTL-like objectives.
The temporal logic of programs
Amir Pnueli · 1977
Earlier work this paper cites.
A theory of the learnable
L. G. Valiant · 1984
Earlier work this paper cites.
A hierarchy of temporal properties
Zohar Manna and Amir Pnueli · 1987
Earlier work this paper cites.
A hierarchy of temporal properties
Zohar Manna and Amir Pnueli · 1987
Earlier work this paper cites.
On the complexity of ω \omega -automata
S. Safra · 1988
Earlier work this paper cites.
Learning to predict by the methods of temporal differences
Richard S. Sutton · 1988
Earlier work this paper cites.
Q-learning
Christopher J. C. H. Watkins and Peter Dayan · 1992
Earlier work this paper cites.
Efficient reinforcement learning
Claude-Nicolas Fiechter · 1994
Earlier work this paper cites.
Markov Decision Processes—Discrete Stochastic Dynamic Programming
Martin L. Puterman · 1994
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Richard S. Sutton and Andrew G. Barto · 1998
Earlier work this paper cites.
Approximate planning in large pomdps via reusable trajectories
Michael Kearns, Yishay Mansour, and Andrew Y. Ng · 1999
Earlier work this paper cites.
Model checking of safety properties
Orna Kupferman and Moshe Vardi · 1999
Earlier work this paper cites.
Near-optimal reinforcement learning in polynomial time
Michael Kearns and Satinder Singh · 2002
Earlier work this paper cites.
On the Sample Complexity of Reinforcement Learning
Sham M. Kakade · 2003
Earlier work this paper cites.
Efficient model checking of safety properties
Timo Latvala · 2003
Earlier work this paper cites.
Pac model-free reinforcement learning
Alexander Strehl, Lihong Li, Eric Wiewiora, John Langford, and Michael Littman · 2006
Earlier work this paper cites.
Collision avoidance for unmanned aircraft using markov decision processes
Selim Temizer, Mykel Kochenderfer, Leslie Kaelbling, Tomas Lozano-Perez, and James Kuchar · 2010
Earlier work this paper cites.
Double q-learning
H. V. Hasselt · 2010
Earlier work this paper cites.
Statistical model checking for markov decision processes
David Henriques, João G. Martins, Paolo Zuliani, André Platzer, and Edmund M. Clarke · 2012
Earlier work this paper cites.
Statistical model checking for markov decision processes
David Henriques, João G. Martins, Paolo Zuliani, André Platzer, and Edmund M. Clarke · 2012
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Reinforcement learning in robotics: A survey
Jens Kober, J. Bagnell, and Jan Peters · 2013
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Linear temporal logic and linear dynamic logic on finite traces
Giuseppe De Giacomo and Moshe Y. Vardi · 2013
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Verification of markov decision processes using learning algorithms
Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelík, Vojtěch Forejt, Jan Křetínský, Marta Kwiatkowska, David Parker, and Mateusz Ujma · 2014
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Reinforcement learning and the reward engineering principle
Dan Dewey · 2014
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Probably approximately correct MDP learning and control with temporal logic constraints
Jie Fu and Ufuk Topcu · 2014
Policy certificates: Towards accountable reinforcement learning
Christoph Dann, Lihong Li, Wei Wei, and Emma Brunskill · 2019
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Foundations for restraining bolts: Reinforcement learning with ltlf/ldlf restraining specifications
Giuseppe De Giacomo, L. Iocchi, Marco Favorito, and F. Patrizi · 2019
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Omega-regular objectives in model-free reinforcement learning
Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, and Dominik Wojtczak · 2019
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Reinforcement learning for temporal logic control synthesis with probabilistic satisfaction guarantees
M. Hasanbeig, Yiannis Kantaros, A. Abate, D. Kroening, George Pappas, and I. Lee · 2019
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A composable specification language for reinforcement learning tasks
Kishor Jothimurugan, R. Alur, and Osbert Bastani · 2019
Later among the works it cites.
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Cited alongside, same era.
A learning based approach to control synthesis of markov decision processes for linear temporal logic specifications
Dorsa Sadigh, Eric S. Kim, Samuel Coogan, S. Shankar Sastry, and Sanjit A. Seshia · 2014
Cited alongside, same era.
Verification of markov decision processes using learning algorithms
Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelík, Vojtěch Forejt, Jan Křetínský, Marta Kwiatkowska, David Parker, and Mateusz Ujma · 2014
Cited alongside, same era.
Probably approximately correct MDP learning and control with temporal logic constraints
Jie Fu and Ufuk Topcu · 2014
Cited alongside, same era.
A learning based approach to control synthesis of markov decision processes for linear temporal logic specifications
Dorsa Sadigh, Eric S. Kim, Samuel Coogan, S. Shankar Sastry, and Sanjit A. Seshia · 2014
Cited alongside, same era.
Blazing the trails before beating the path: Sample-efficient monte-carlo planning
Jean-Bastien Grill, Michal Valko, and R. Munos · 2016
Cited alongside, same era.
Spot 2.0 - a framework for ltl and ω \omega -automata manipulation
Alexandre Duret-Lutz, Alexandre Lewkowicz, Amaury Fauchille, Thibaud Michaud, Etienne Renault, and Laurent Xu · 2016
Cited alongside, same era.
Pac statistical model checking for markov decision processes and stochastic games
Pranav Ashok, Jan Křetínský, and Maximilian Weininger · 2019
Later among the works it cites.
Ltl and beyond: Formal languages for reward function specification in reinforcement learning
Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, and Sheila A. McIlraith · 2019
Later among the works it cites.
Policy certificates: Towards accountable reinforcement learning
Christoph Dann, Lihong Li, Wei Wei, and Emma Brunskill · 2019
Later among the works it cites.
Foundations for restraining bolts: Reinforcement learning with ltlf/ldlf restraining specifications
Giuseppe De Giacomo, L. Iocchi, Marco Favorito, and F. Patrizi · 2019
Later among the works it cites.
Omega-regular objectives in model-free reinforcement learning
Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, and Dominik Wojtczak · 2019
Later among the works it cites.
Reinforcement learning for temporal logic control synthesis with probabilistic satisfaction guarantees
M. Hasanbeig, Yiannis Kantaros, A. Abate, D. Kroening, George Pappas, and I. Lee · 2019
Later among the works it cites.
A composable specification language for reinforcement learning tasks
Kishor Jothimurugan, R. Alur, and Osbert Bastani · 2019
Later among the works it cites.
Control synthesis from linear temporal logic specifications using model-free reinforcement learning
Alper Bozkurt, Yu Wang, Michael Zavlanos, and Miroslav Pajic · 2020
Later among the works it cites.
Temporal-logic-based reward shaping for continuing learning tasks
Yuqian Jiang, Sudarshanan Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone · 2020
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Control synthesis from linear temporal logic specifications using model-free reinforcement learning
Alper Bozkurt, Yu Wang, Michael Zavlanos, and Miroslav Pajic · 2020
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Faithful and effective reward schemes for model-free reinforcement learning of omega-regular objectives
Ernst Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, and Dominik Wojtczak · 2020
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A framework for transforming specifications in reinforcement learning
Rajeev Alur, Suguman Bansal, Osbert Bastani, and Kishor Jothimurugan · 2021
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A framework for transforming specifications in reinforcement learning
Rajeev Alur, Suguman Bansal, Osbert Bastani, and Kishor Jothimurugan · 2021
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Mungojerrie: Reinforcement learning of linear-time objectives
Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, and Dominik Wojtczak · 2021
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