Fetching the paper…
Reading the bibliography…
We consider synthesis of control policies that maximize the probability of satisfying given temporal logic specifications in unknown, stochastic environments.
A. Bianco and L. De Alfaro, “Model checking of probabilistic and nondeterministic systems,” in Foundations of Software Technology and Theoretical Computer Science
1995
Earlier work this paper cites.
PhD thesis, Stanford University, 1997
L. De Alfaro, Formal Verification of Probabilistic Systems · 1997
Earlier work this paper cites.
M. Kearns and S. Singh, “Near-optimal reinforcement learning in polynomial time,” Machine Learning
2002
Earlier work this paper cites.
PhD thesis, University of Massachusetts Amherst, 2002
M. O. Duff, Optimal Learning: Computational Procedures for Bayes-adaptive Markov Decision Processes · 2002
Earlier work this paper cites.
R. Brafman and M. Tennenholtz, “R-MAX-a general polynomial time algorithm for near-optimal reinforcement learning,” The Journal of Machine Learning
2003
Earlier work this paper cites.
American Mathematical Society, 2004
J. Rutten, M. Kwiatkowska, G. Norman, and D. Parker, Mathematical Techniques for Analyzing Concurrent and Probabilistic Systems, · 2004
Earlier work this paper cites.
C. Baier, M. Größer, M. Leucker, B. Bollig, and F. Ciesinski, “Controller Synthesis for Probabilistic Systems (Extended Abstract),” in Exploring New Frontiers of Theoretical Informatics
2004
Earlier work this paper cites.
Wiley, 2004
N. Balakrishnan and V. B. Nevzorov, A Primer on Statistical Distributions · 2004
Cited alongside, same era.
T. Wang, D. Lizotte, M. Bowling, and D. Schuurmans, “Bayesian sparse sampling for on-line reward optimization,” in Proceedings of the 22nd International Conference on Machine Learning
2005
Cited alongside, same era.
A. L. Strehl, L. Li, E. Wiewiora, J. Langford, and M. L. Littman, “PAC model-free reinforcement learning,” in Proceedings of the 23rd International Conference on Machine Learning
2006
Cited alongside, same era.
P. S. Castro and D. Precup, “Using linear programming for bayesian exploration in markov decision processes,” in International Joint Conferences on Artificial Intelligence
2007
Cited alongside, same era.
A. Legay, B. Delahaye, and S. Bensalem, “Statistical model checking: An overview,” in Runtime Verification
2010
Cited alongside, same era.
D. Henriques, J. G. Martins, P. Zuliani, A. Platzer, and E. M. Clarke, “Statistical model checking for Markov decision processes,” International Conference on Quantitative Evaluation of Systems
2012
Later among the works it cites.
Y. Chen, J. Tumova, and C. Belta, “LTL robot motion control based on automata learning of environmental dynamics,” in IEEE International Conference on Robotics and Automation
2012
Later among the works it cites.
H. Mao, Y. Chen, M. Jaeger, T. D. Nielsen, K. G. Larsen, and B. Nielsen, “Learning markov decision processes for model checking,” in Proceedings of Quantities in Formal Methods
2012
Later among the works it cites.
K. Chatterjee, M. Henzinger, M. Joglekar, and N. Shah, “Symbolic algorithms for qualitative analysis of Markov decision processes with Büchi objectives,” Formal Methods in System Design
2012
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cambridge University Press Textbooks, 2011
B. L. Mark and W. Turin, Probability, Random Processes, and Statistical Analysis · 2011
Cited alongside, same era.
E. M. Wolff, U. Topcu, and R. M. Murray, “Optimal control with weighted average costs and temporal logic specifications.,” in Robotics: Science and Systems
2012
Later among the works it cites.
J. Fu, H. G. Tanner, and J. Heinz, “Adaptive planning in unknown environments using grammatical inference,” in IEEE Conference on Decision and Control
2013
Later among the works it cites.