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We present a simulation-based approach for generating barrier certificate functions for safety verification of cyber-physical systems (CPS) that contain neural network-based controllers.
Evolutionary computation
Nikolaus Hansen & Andreas Ostermeier (2001): Completely derandomized self-adaptation in evolution strategies · 2001
Earlier work this paper cites.
In: Evolutionary Computation, 2003. CEC’03. The 2003 Congress on
Christian Igel (2003): Neuroevolution for reinforcement learning using evolution strategies · 2003
Earlier work this paper cites.
In: In Hybrid Systems: Computation and Control
Stephen Prajna & Ali Jadbabaie (2004): Safety Verification of Hybrid Systems Using Barrier Certificates · 2004
Earlier work this paper cites.
Ph.D. thesis, California Institute of Technology, Caltech, Pasadena, CA, USA
Stephen Prajna (2005): Optimization-based methods for nonlinear and hybrid systems verification · 2005
Earlier work this paper cites.
In: Logic in Computer Science
Sicun Gao, Jeremy Avigad & Edmund Clarke (2012): Delta-Complete Decision Procedures for Satisfiability over the Reals · 2012
Earlier work this paper cites.
In: International Conference on Automated Deduction
Sicun Gao, Soonho Kong & Edmund M Clarke (2013): dReal: An SMT solver for nonlinear theories over the reals · 2013
Cited alongside, same era.
In: Hybrid Systems: Computation and Control
James Kapinski, Jyotirmoy V. Deshmukh, Sriram Sankaranarayanan & Nikos Aréchiga (2014): Simulation-guided Lyapunov Analysis for Hybrid Dynamical Systems · 2014
Cited alongside, same era.
In: Proc. of the 1st Indian Control Conference
Ayca Balkan, Jyotirmoy V Deshmukh, James Kapinski & Paulo Tabuada (2015): Simulation-guided Contraction Analysis · 2015
Cited alongside, same era.
In: NASA Formal Methods Symposium
Tommaso Dreossi, Alexandre Donzé & Sanjit A Seshia (2017): Compositional falsification of cyber-physical systems with machine learning components · 2017
Cited alongside, same era.
arXiv preprint arXiv:1709.09130
Souradeep Dutta, Susmit Jha, Sriram Sanakaranarayanan & Ashish Tiwari (2017): Output Range Analysis for Deep Neural Networks · 2017
Cited alongside, same era.
In: International Symposium on Automated Technology for Verification and Analysis
Ruediger Ehlers (2017): Formal verification of piece-wise linear feed-forward neural networks · 2017
Later among the works it cites.
In: International Conference on Computer Aided Verification
Xiaowei Huang, Marta Kwiatkowska, Sen Wang & Min Wu (2017): Safety verification of deep neural networks · 2017
Later among the works it cites.
In: International Conference on Computer Aided Verification
Guy Katz, Clark Barrett, David L Dill, Kyle Julian & Mykel J Kochenderfer (2017): Reluplex: An efficient SMT solver for verifying deep neural networks · 2017
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ACM Transactions on Embedded Computing Systems (TECS)
Ayca Balkan, Paulo Tabuada, Jyotirmoy V Deshmukh, Xiaoqing Jin & James Kapinski (2018): Underminer: A Framework for Automatically Identifying Nonconverging Behaviors in Black-Box System Models · 2018
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