Roman Andriushchenko

Publication Results

• 2025

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; CHAKRABORTY, D.; JUNGES, S.; KRETINSKY, J.; MACÁK, F. Symbiotic Local Search for Small Decision Tree Policies in MDPs. In Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence. Proceedings of Machine Learning Research. ML Research Press, 2025. p. 132-142. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; MACÁK, F. Small Decision Trees for MDPs with Deductive Synthesis. In Computer Aided Verification. Springer Cham, 2025. p. 169-192. ISBN: 978-3-031-98678-9. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; MACÁK, F.; FRANCESCO, P.; MICHELE, C. Decentralized Planning Using Probabilistic Hyperproperties. In Proc. of the 24th International Conference on Autonomous Agents and Multiagent Systems. Detroit: 2025. p. 1688-1697. ISBN: 979-8-4007-1426-9. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; MACÁK, F.; JUNGES, S. Policies Grow on Trees: Model Checking Families of MDPs. In Proceeding of 22nd International Symposium on Automated Technology for Verification and Analysis. Cham: Springer Verlag, 2025. p. 51-75. ISBN: 978-3-031-78749-2. Detail

  GALESLOOT, M.; ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; JANSEN, N. Robust Finite-Memory Policy Gradients for Hidden-Model POMDPs. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2025. p. 8518-8526. ISBN: 978-1-956792-06-5. Detail

  MACÁK, F.; ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; KATOEN, J. An Oracle-Guided Approach to Constrained Policy Synthesis Under Uncertainty. The journal of artificial intelligence research, 2025, vol. 2025, iss. 82, p. 433-469. Detail

• 2024

  ČEŠKA, M.; ANDRIUSHCHENKO, R.; ARND, H.; JUNGES, S.; KŘETÍNSKÝ, J. Tools at the Frontiers of Quantitative Verification: QComp 2023 Competition Report. In International TOOLympics Challenge. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland AG, 2024. p. 90-146. ISBN: 978-3-031-67694-9. Detail

  HELFRICH, M.; ANDRIUSHCHENKO, R.; ČEŠKA, M.; KŘETÍNSKÝ, J.; MARTIČEK, Š.; ŠAFRÁNEK, D. Abstraction-based segmental simulation of reaction networks using adaptive memoization. BMC BIOINFORMATICS, 2024, vol. 25, iss. 1, p. 1-24. ISSN: 1471-2105. Detail

• 2023

  ANDRIUSHCHENKO, R.; ALEXANDER, B.; ČEŠKA, M.; JUNGES, S.; KATOEN, J.; MACÁK, F. Search and Explore: Symbiotic Policy Synthesis in POMDPs. In Computer Aided Verification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Cham: Springer Verlag, 2023. p. 113-135. ISBN: 978-3-031-37708-2. Detail

  ANDRIUSHCHENKO, R.; BARTOCCI, E.; ČEŠKA, M.; FRANCESCO, P.; SARAH, S. Deductive Controller Synthesis for Probabilistic Hyperproperties. In Quantitative Evaluation of SysTems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Cham: Springer Verlag, 2023. p. 288-306. ISBN: 978-3-031-43834-9. Detail

• 2022

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; KATOEN, J. Inductive Synthesis of Finite-State Controllers for POMDPs. In Conference on Uncertainty in Artificial Intelligence. Proceedings of Machine Learning Research. Proceedings of Machine Learning Research. Eindhoven: Proceedings of Machine Learning Research, 2022. iss. 180, p. 85-95. ISSN: 2640-3498. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; MARCIN, V.; VOJNAR, T. GPU-Accelerated Synthesis of Probabilistic Programs. In International Conference on Computer Aided Systems Theory (EUROCAST'22). Lecture Notes in Computer Science. Cham: Springer Nature Switzerland AG, 2022. p. 256-266. ISBN: 978-3-031-25312-6. Detail

• 2021

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; ABATE, A.; KWIATKOWSKA, M. Adaptive formal approximations of Markov chains. PERFORMANCE EVALUATION, 2021, vol. 148, iss. 102207, p. 1-23. ISSN: 0166-5316. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; KATOEN, J. Inductive Synthesis for Probabilistic Programs Reaches New Horizons. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS). Lecture Notes in Computer Science. Cham: Springer International Publishing, 2021. p. 191-209. ISBN: 978-3-030-72015-5. Detail

  ANDRIUSHCHENKO, R.; ČEŠKA, M.; STUPINSKÝ, Š.; JUNGES, S.; KATOEN, J. PAYNT: A Tool for Inductive Synthesis of Probabilistic Programs. In International Conference on Computer Aided Verification (CAV). Lecture Notes in Computer Science. Cham: Springer Verlag, 2021. p. 856-869. ISBN: 978-3-030-81684-1. Detail