Chatterjee, K., Chmelik, M., Karkhanis, D., Novotný, P., &; Royer, A. (2020). Multiple-environment Markov decision processes: Efficient analysis and applications. In Proceedings of the 30th International Conference on Automated Planning and Scheduling (Vol. 30, pp. 48–56). Nancy, France: Association for the Advancement of Artificial Intelligence.

Svoreová, M., Kretinsky, J., Chmelik, M., Chatterjee, K., Cbrná, I., &; Belta, C. (2017). Temporal logic control for stochastic linear systems using abstraction refinement of probabilistic games. Nonlinear Analysis: Hybrid Systems. Elsevier.https://doi.org/10.1016/j.nahs.2016.04.006 

Chatterjee, K., &; Chmelik, M. (2016). Indefinite-horizon reachability in Goal-DEC-POMDPs. In Proceedings of the Twenty-Sixth International Conference on International Conference on Automated Planning and Scheduling (Vol. 2016–January, pp. 88–96). London, United Kingdom: AAAI Press.

Brázdil, T., Chatterjee, K., Chmelik, M., Gupta, A., &; Novotný, P. (2016). Stochastic shortest path with energy constraints in POMDPs. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (pp. 1465–1466). Singapore: ACM.

Lohse, K., Chmelik, M., Martin, S., &; Barton, N. H. (2016). Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.115.183814 

Chatterjee, K., Chmelik, M., &; Tracol, M. (2016). What is decidable about partially observable Markov decision processes with <9-regular objectives. Journal of Computer and System Sciences. Elsevier.https://doi.org/10.1016/j.jcss.2016.02.009 

Chatterjee, K., Chmelik, M., Gupta, R., &; Kanodia, A. (2016). Optimal cost almost-sure reachability in POMDPs. Artificial Intelligence. Elsevier.https://doi.org/10.1016/j.artint.2016.01.007 

Chatterjee, K., Chmelik, M., &; Davies, J. (2016). A symbolic SAT based algorithm for almost sure reachability with small strategies in pomdps. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (Vol. 2016, pp. 3225–3232). Phoenix, AZ, USA: AAAI Press.

Chmelik, M. (2016). Algorithms for partially observable markov decision processes. Institute of Science and Technology Austria.

Svoreová, M., Chmelik, M., Leahy, K., Eniser, H., Chatterjee, K., Cbrná, I., &; Belta, C. (2015). Temporal logic motion planning using POMDPs with parity objectives: Case study paper. In Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control (pp. 233–238). Seattle, WA, United States: ACM.https://doi.org/10.1145/2728606.2728617 

Chatterjee, K., Chmelik, M., Gupta, R., &; Kanodia, A. (2015). Optimal cost almost-sure reachability in POMDPs. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence  (Vol. 5, pp. 3496–3502). Austin, TX, USA: AAAI Press.

Chatterjee, K., &; Chmelik, M. (2015). POMDPs under probabilistic semantics. Artificial Intelligence. Elsevier.https://doi.org/10.1016/j.artint.2014.12.009 

Chatterjee, K., Chmelik, M., Gupta, R., &; Kanodia, A. (2015). Qualitative analysis of POMDPs with temporal logic specifications for robotics applications (pp. 325–330). Presented at the ICRA: International Conference on Robotics and Automation, Seattle, WA, United States: IEEE.https://doi.org/10.1109/ICRA.2015.7139019 

Chatterjee, K., Chmelik, M., &; Davies, J. (2015). A symbolic SAT-based algorithm for almost-sure reachability with small strategies in POMDPs. IST Austria.https://doi.org/10.15479/AT:IST-2015-325-v2-1 

Chatterjee, K., Chmelik, M., &; Daca, P. (2015). CEGAR for compositional analysis of qualitative properties in Markov decision processes. Formal Methods in System Design. Springer.https://doi.org/10.1007/s10703-015-0235-2 

Svoreová, M., Kretinsky, J., Chmelik, M., Chatterjee, K., Cbrná, I., &; Belta, C. (2015). Temporal logic control for stochastic linear systems using abstraction refinement of probabilistic games. In Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control (pp. 259–268). Seattle, WA, United States: ACM.https://doi.org/10.1145/2728606.2728608 

Brázdil, T., Chatterjee, K., Chmelik, M., Fellner, A., &; Kretinsky, J. (2015). Counterexample explanation by learning small strategies in Markov decision processes (Vol. 9206, pp. 158–177). Presented at the CAV: Computer Aided Verification, San Francisco, CA, United States: Springer.https://doi.org/10.1007/978-3-319-21690-4_10 

Brázdil, T., Chatterjee, K., Chmelik, M., Forejt, V., Kretinsky, J., Kwiatkowska, M.,https://doi.org/10.1007/978-3-319-11936-6_8__Ujma, M. (2014). Verification of markov decision processes using learning algorithms. In F. Cassez &; J.-F. Raskin (Eds.), https://doi.org/10.1007/978-3-319-11936-6_8__Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8837, pp. 98–114). Sydney, Australia: Society of Industrial and Applied Mathematics.https://doi.org/10.1007/978-3-319-11936-6_8 

Cerny, P., Chmelik, M., Henzinger, T. A., &; Radhakrishna, A. (2014). Interface simulation distances. Theoretical Computer Science. Elsevier.https://doi.org/10.1016/j.tcs.2014.08.019 

Chatterjee, K., Daca, P., &; Chmelik, M. (2014). CEGAR for qualitative analysis of probabilistic systems. IST Austria.https://doi.org/10.15479/AT:IST-2014-153-v2-2