Learning control lyapunov functions from counterexamples and demonstrations

Author:

Ravanbakhsh Hadi,Sankaranarayanan Sriram

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Reference106 articles.

1. Abbas, H., Fainekos, G., Sankaranarayanan, S., Ivancic, F., & Gupta, A. (2013). Probabilistic temporal logic falsification of cyber-physical systems. Transactions on Embedded Computing Systems (TECS), 12, 95.

2. Ahmadi, A. A., & Majumdar, A. (2014). DSOS and SDSOS optimization: LP and SOCP-based alternatives to sum of squares optimization. In 2014 48th annual conference on information sciences and systems (CISS) (pp. 1–5). IEEE.

3. Ames, A. D., & Powell, M. (2013). Towards the unification of locomotion and manipulation through control Lyapunov functions and quadratic programs. In D. C. Tarraf (Ed.), Control of cyber-physical systems: workshop held at Johns Hopkins University (pp. 219–240). Heidelberg: Springer.

4. Annpureddy, Y., Liu, C., Fainekos, G. E., & Sankaranarayanan, S. (2011). S-TaLiRo: A tool for temporal logic falsification for hybrid systems. In P. A. Abdulla, & K. R. M. Leino (Eds.), Tools and algorithms for the construction and analysis of systems, LNCS (Vol. 6605, pp. 254–257). Berlin, Heidelberg: Springer.

5. Argall, B. D., Chernova, S., Veloso, M., & Browning, B. (2009). A survey of robot learning from demonstration. Robotics and Autonomous Systems, 57(5), 469–483. https://doi.org/10.1016/j.robot.2008.10.024 .

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