Visible to the public Resilient Control of Cyber-Physical Systems with Distributed Learning - July 2021Conflict Detection Enabled

PI(s) and Co-PI(s): Sayan Mitra and Geir Dullerud and Sanjay Shakkotai (U. Texas at Austin)

Researchers: Dawei Sun and Negin Musavi

This refers to Hard Problems, released November 2012.

Resiliency: Effective verification of safety and security properties of autonomous and cyber-physical systems

Metrics: How much data is necessary to achieve a certain level of confidence regarding a safety/security claim

Papers written as a result of your research from the current quarter only.

Papers in preparation and submission:

Verification and Parameter Synthesis for Stochastic Systems using Optimistic Optimization, Negin Musavi, Dawei Sun, Sayan Mitra, Sanjay Shakkottai, and Geir Dullerud, to appear in Proceedings of IEEE Conference on Control Technology and Applications (CCTA), September 2021.

Continuous Integration and Testing for Autonomous Racing Software: An Experience Report from GRAIC, Minghao Jiang, Kristina Miller, Dawei Sun, Zexiang Liu, Yixuan Jia, Arnab Datta, Necmiye Ozay and Sayan Mitra. Contributed paper in ICRA 21 Workshop on Opportunities and Challenges with Autonomous Racing, 31 May, 2021.

Egocentric abstractions for verification of distributed cyber-physical systems. Sung Woo Jeon and Sayan Mitra. IEEE Workshop on the Internet of Safe Things (SafeThings'21), co-located with Oakland, 2021. Won the Best Paper Award.

NeuReach: Learning Reachability Functions from Simulations, Dawei Sun and Sayan Mitra, in preparation, February 2021.

Policy Optimization for Markovian Jump Linear Quadratic Control: Gradient-Based Methods and Global Convergence

and Parameter Synthesis for Stochastic Systems using Optimistic Optimization, Joao Jansch-Porto, Bin Hu, and Geir Dullerud, submitted for review, January 2021.

Verifying Stochastic Hybrid Systems with Temporal Logic Specifications via Model Reduction, Yu Wang, Y., Nima Roohi, Matt West, Mahesh Viswanathan, and Geir Dullerud, submitted to Transactions on Embedded Computing Sys- tems, May 2021.

Linear Bandit Algorithms with Sublinear Time Complexity, Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit Dhillon and Sujay Sanghavi, submitted for review, February 2021.

Related recent and forthcoming publications:

Optimistic Optimization for Statistical Model Checking with Regret Bounds, Negin Musavi, Dawei Sun, Sayan Mitra, Sanjay Shakkottai, and Geir Dullerud, July 2020. Presented at the workshop on Symbolic and Numerical methods for Reasoning about Cyber-Physical Systems.

Full version available online from HOOVER tool available from:

Verifying Cyber-Physical Systems: A Path to Safe Autonomy, Sayan Mitra, Published by MIT Press, February 16, 2021.

Warm Starting Bandits with Side Information from Confounded Data, N. Sharma, S. Basu, K. Shanmugam and S. Shakkottai, arXiv 2002.08405, 2020. Available at:

L2-gain Analysis of Periodic, Event-Triggered Control and Self-Triggered Control using Lifting, N. Strijbosch, G.E.Dullerud, A.Teel, M.Heemels", to appear IEEE Transactions on Automatic Control, 2021.

Each effort should submit one or two specific highlights. Each item should include a paragraph or two along with a citation if available. Write as if for the general reader of IEEE S&P.
The purpose of the highlights is to give our immediate sponsors a body of evidence that the funding they are providing (in the framework of the SoS lablet model) is delivering results that "more than justify" the investment they are making.

We are developing safety and security analysis approaches for real-life of autonomous and cyber-physical systems using statistical and machine learning techniques. Our approaches rely on distributed and sample-efficient optimization techniques that have been developed in the context of the Multi-armed bandit problem. We have shown how these optimization algorithms can be used effectively for statistical model checking of markov decision processes and hybrid systems. We have built a suite of benchmarks related to online safety analysis of autonomous and semi-autonomous vehicles. Our initial results are very promising as the data usage and the running time of our algorithms can be several orders of magnitude better than existing model checking approaches such as Storm and Prism. Two PhD students are dedicating their research time to the project and the prototype tool has been made available online.


We developed and organized the GRAIC Autonomous Racing Competition which was co-located with CPSWeek 2021. The live event had more than 80 registered members and 30+ attendees. The software framework has been made available to the community for research.

Invited lectures: Mitra

  • Interfaces for models and data in verification and synthesis. Workshop on Learning and Control, and seminars co-located with CPS-IoTWeek 21, chaired by Rafal Wisniewski and Manuela Bujorianu, May 18, 2021.
  • Data requirements for estimation and verification. Simons Institute, Theoretical Foundations of Computer Science Seminar, May 11, 2021.
  • Mitra participated in a panel discussion at the AFCEA Ideation and Innovation Virtual Event. March 10, 2021. Panel discussion on state of the art and challenges in implementing autonomy


None to report.