Convergence proofs for Simulated Annealing falsification of safety properties

The problem of falsifying temporal logic properties of hybrid automata can be posed as a minimization problem by utilizing quantitative semantics for temporal logics. Previous work has used a variation of Simulated Annealing (SA) to solve the problem. While SA is known to converge to the global minimum of a continuous objective function over a closed and bounded search space, or when the search space is discrete, there do not exist convergence proofs for the cases addressed in that previous work. Namely, when the objective function is discontinuous, and when the objective is a vector-valued function. In this paper, we derive conditions and we prove convergence of SA to a global minimum in both scenarios. We also consider matters affecting the practical performance of SA.

[1]  François Fages,et al.  On a Continuous Degree of Satisfaction of Temporal Logic Formulae with Applications to Systems Biology , 2008, CMSB.

[2]  Paulo Tabuada,et al.  Verification and Control of Hybrid Systems - A Symbolic Approach , 2009 .

[3]  Piotr Czyzżak,et al.  Pareto simulated annealing—a metaheuristic technique for multiple‐objective combinatorial optimization , 1998 .

[4]  Edmund M. Clarke,et al.  Bayesian statistical model checking with application to Stateflow/Simulink verification , 2010, Formal Methods in System Design.

[5]  Houssam Abbas,et al.  Linear Hybrid System Falsification through Local Search , 2011, ATVA.

[6]  Antoine Girard,et al.  Approximation Metrics for Discrete and Continuous Systems , 2006, IEEE Transactions on Automatic Control.

[7]  Pravin Varaiya,et al.  What's decidable about hybrid automata? , 1995, STOC '95.

[8]  Karl Henrik Johansson,et al.  Dynamical properties of hybrid automata , 2003, IEEE Trans. Autom. Control..

[9]  Ricardo G. Sanfelice,et al.  Dynamical properties of hybrid systems simulators , 2010, Autom..

[10]  Claude J. P. Bélisle Convergence theorems for a class of simulated annealing algorithms on ℝd , 1992 .

[11]  Edmund M. Clarke,et al.  Verification of Supervisory Control Software Using State Proximity and Merging , 2008, HSCC.

[12]  Joshua A. Levine,et al.  Sampling-based planning, control and verification of hybrid systems , 2000 .

[13]  Sriram Sankaranarayanan,et al.  Monte-carlo techniques for falsification of temporal properties of non-linear hybrid systems , 2010, HSCC '10.

[14]  John Lygeros,et al.  Stochastic Optimization on Continuous Domains With Finite-Time Guarantees by Markov Chain Monte Carlo Methods , 2009, IEEE Transactions on Automatic Control.

[15]  Tarik Nahhal,et al.  Test Coverage for Continuous and Hybrid Systems , 2007, CAV.

[16]  Chris Murphy,et al.  Dominance-Based Multiobjective Simulated Annealing , 2008, IEEE Transactions on Evolutionary Computation.

[17]  Qianchuan Zhao,et al.  Generating test inputs for embedded control systems , 2003 .

[18]  Oded Maler,et al.  Systematic Simulation Using Sensitivity Analysis , 2007, HSCC.

[19]  Lydia E. Kavraki,et al.  Falsification of LTL Safety Properties in Hybrid Systems , 2009, TACAS.

[20]  Sriram Sankaranarayanan,et al.  S-TaLiRo: A Tool for Temporal Logic Falsification for Hybrid Systems , 2011, TACAS.

[21]  Sriram Sankaranarayanan,et al.  Probabilistic Temporal Logic Falsification of Cyber-Physical Systems , 2013, TECS.

[22]  Sheldon Howard Jacobson,et al.  The Theory and Practice of Simulated Annealing , 2003, Handbook of Metaheuristics.

[23]  George J. Pappas,et al.  Robustness of temporal logic specifications for continuous-time signals , 2009, Theor. Comput. Sci..

[24]  Paulo Tabuada,et al.  Verification and Control of Hybrid Systems , 2009 .

[25]  Lydia E. Kavraki,et al.  Hybrid Systems: From Verification to Falsification , 2007, CAV.

[26]  Bruce E. Hajek,et al.  Cooling Schedules for Optimal Annealing , 1988, Math. Oper. Res..

[27]  Stefan Ratschan,et al.  Finding Errors of Hybrid Systems by Optimising an Abstraction-Based Quality Estimate , 2009, TAP@TOOLS.

[28]  R. Sanfelice,et al.  Hybrid dynamical systems , 2009, IEEE Control Systems.