Graham, T., Kleshnina, M., &; Filar, J. A. (2023). Where do mistakes lead? A survey of games with incompetent players. Dynamic Games and Applications. Springer Nature.https://doi.org/10.1007/s13235-022-00425-3 

Baier, C., Chatterjee, K., Meggendorfer, T., &; Piribauer, J. (2023). Entropic risk for turn-based stochastic games. In 48th International Symposium on Mathematical Foundations of Computer Science (Vol. 272). Bordeaux, France: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.MFCS.2023.15 

Mckerral, J. C., Kleshnina, M., Ejov, V., Bartle, L., Mitchell, J. G., &; Filar, J. A. (2023). Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur equations. PLoS One. Public Library of Science.https://doi.org/10.1371/journal.pone.0279838 

Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., &; Zikelic, D. (2023). Reachability poorman discrete-bidding games. In Frontiers in Artificial Intelligence and Applications (Vol. 372, pp. 141–148). Krakow, Poland: IOS Press.https://doi.org/10.3233/FAIA230264 

Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., &; Zikelic, D. (2023). Learning provably stabilizing neural controllers for discrete-time stochastic systems. In 21st International Symposium on Automated Technology for Verification and Analysis (Vol. 14215, pp. 357–379). Singapore, Singapore: Springer Nature.https://doi.org/10.1007/978-3-031-45329-8_17 

Schmid, S., Svoboda, J., &; Yeo, M. X. (2023). Weighted packet selection for rechargeable links in cryptocurrency networks: Complexity and approximation. In SIROCCO 2023: Structural Information and Communication Complexity  (Vol. 13892, pp. 576–594). Alcala de Henares, Spain: Springer Nature.https://doi.org/10.1007/978-3-031-32733-9_26 

Tkadlec, J., Kaveh, K., Chatterjee, K., &; Nowak, M. A. (2023). Evolutionary dynamics of mutants that modify population structure. Journal of the Royal Society, Interface. The Royal Society.https://doi.org/10.1098/rsif.2023.0355 

Kleshnina, M., Hilbe, C., Simsa, S., Chatterjee, K., &; Nowak, M. A. (2023). The effect of environmental information on evolution of cooperation in stochastic games. Nature Communications. Springer Nature.https://doi.org/10.1038/s41467-023-39625-9 

Kleshnina, M. (2023). kleshnina/stochgames_info: The effect of environmental information on evolution of cooperation in stochastic games. Zenodo.https://doi.org/10.5281/ZENODO.8059564 

Kretinsky, J., Meggendorfer, T., &; Weininger, M. (2023). Stopping criteria for value iteration on stochastic games with quantitative objectives. In 38th Annual ACM/IEEE Symposium on Logic in Computer Science (Vol. 2023). Boston, MA, United States: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/LICS56636.2023.10175771 

Biniaz, A., Jain, K., Lubiw, A., Masárová, Z., Miltzow, T., Mondal, D.,https://doi.org/10.46298/DMTCS.8383__Turcotte, A. (2023). Token swapping on trees. Discrete Mathematics and Theoretical Computer Science. EPI Sciences.https://doi.org/10.46298/DMTCS.8383 

Bastankhah, M., Chatterjee, K., Maddah-Ali, M. A., Schmid, S., Svoboda, J., &; Yeo, M. X. (2023). : Boosting liquidity in payment channel networks with online admission control. In 27th International Conference on Financial Cryptography and Data Security (Vol. 13950, pp. 309–325). Bol, Brac, Croatia: Springer Nature.https://doi.org/10.1007/978-3-031-47754-6_18 

Zikelic, D. (2023). Automated verification and control of infinite state stochastic systems. Institute of Science and Technology Austria.https://doi.org/10.15479/14539 

Kisan, J. M., &; Svoboda, J. (2023). Shortest dominating set reconfiguration under token sliding. In 24th International Symposium on Fundamentals of Computation Theory (Vol. 14292, pp. 333–347). Trier, Germany: Springer Nature.https://doi.org/10.1007/978-3-031-43587-4_24 

Zikelic, D., Lechner, M., Henzinger, T. A., &; Chatterjee, K. (2023). Learning control policies for stochastic systems with reach-avoid guarantees. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 11926–11935). Washington, DC, United States: Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v37i10.26407 

Meggendorfer, T. (2023). Correct approximation of stationary distributions. In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13993, pp. 489–507). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-30823-9_25 

Meggendorfer, T. (2023). Artefact for: Correct Approximation of Stationary Distributions. Zenodo.https://doi.org/10.5281/ZENODO.7548214 

Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., &; Henzinger, T. A. (2023). Compositional policy learning in stochastic control systems with formal guarantees. In 37th Conference on Neural Information Processing Systems. New Orleans, LO, United States.

Chatterjee, K., Kafshdar Goharshady, E., Novotný, P., Zárevúcky, J., &; Zikelic, D. (2023). On lexicographic proof rules for probabilistic termination. Formal Aspects of Computing. Association for Computing Machinery.https://doi.org/10.1145/3585391 

Ahmadi, A., Chatterjee, K., Goharshady, A. K., Meggendorfer, T., Safavi Hemami, R., &; Zikelic, D. (2022). Algorithms and hardness results for computing cores of Markov chains. In 42nd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (Vol. 250). Madras, India: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.FSTTCS.2022.29