Dave Parker

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David Parker's research focuses on verification: formal techniques for checking that systems function correctly. In particular, he is interested in quantitative verification, which focuses on the analysis of systems with probabilistic and real-time behaviour.

Dr Parker's work spans the development of new theory, algorithms and tools for this area, as well as investigating its applicability to a wide range of areas, including biology and security. He also leads the development of the probabilistic model checking tool PRISM.

20012022

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Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy
  • SDG 11 - Sustainable Cities and Communities

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  • A value-based dynamic learning approach for vehicle dispatch in ride-sharing

    Li, C., Parker, D. & Hao, Q., 30 Jun 2022, (Accepted/In press) 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022). IEEE, (IEEE/RSJ International Conference on Intelligent Robots and Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    2 Downloads (Pure)
  • Correlated equilibria and fairness in concurrent stochastic games

    Kwiatkowska, M., Norman, G., Parker, D. & Santos, G., 30 Mar 2022, TACAS 2022: Tools and Algorithms for the Construction and Analysis of Systems. Fisman, D. & Rosu, G. (eds.). Springer, p. 60–78 (Lecture Notes in Computer Science; no. 13244).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    4 Downloads (Pure)
  • Finite-horizon equilibria for neuro-symbolic concurrent stochastic games

    Yan, R., Santos, G., Duan, X., Parker, D. & Kwiatkowska, M., 28 Sep 2022, Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence: Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, The Netherlands. Cussens, J. & Zhang, K. (eds.). PMLR website: Proceedings of Machine Learning Research, Vol. 180. p. 2170-2180 11 p. (Proceedings of Machine Learning Research; vol. 180).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • Multi-objective controller synthesis with uncertain human preferences

    Chen, S., Boggess, K., Parker, D. & Feng, L., 24 Jun 2022, (E-pub ahead of print) 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS). Los Alamitos, California, Washington, Tokyo: IEEE, Vol. 2022. p. 170-180 11 p. (ACM/IEEE International Conference on Cyber-Physical Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    4 Downloads (Pure)
  • Planning for automated vehicles with human trust

    Sheng, S., Pakdamanian, E., Han, K., Wang, Z., Lenneman, J., Parker, D. & Feng, L., 2 Sep 2022, (E-pub ahead of print) In: ACM Transactions on Cyber-Physical Systems.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File