On the Efficiency of Deciding Probabilistic Automata Weak Bisimulation

Weak probabilistic bisimulation on probabilistic automata can be decided by an algorithm that needs to check a polynomial number of linear programming problems encoding weak transitions. It is hence polynomial, but not guaranteed to be strongly polynomial. In this paper we show that for polynomial rational proba- bilistic automata strong polynomial complexity can be ensured. We further discuss complexity bounds for generic probabilistic automata. Then we consider several practical algorithms and LP transformations that enable an efficient solution for the concrete weak transition problem. This sets the ground for effective compositional minimisation approaches for probabilistic automata and Markov decision processes.

[1]  L. G. H. Cijan A polynomial algorithm in linear programming , 1979 .

[2]  Joost-Pieter Katoen,et al.  Bisimulation Minimisation Mostly Speeds Up Probabilistic Model Checking , 2007, TACAS.

[3]  Roberto Segala Probability and Nondeterminism in Operational Models of Concurrency , 2006, CONCUR.

[4]  Peter A. Beling,et al.  Exact Algorithms for Linear Programming over Algebraic Extensions , 2001, Algorithmica.

[5]  Éva Tardos,et al.  A Strongly Polynomial Algorithm to Solve Combinatorial Linear Programs , 1986, Oper. Res..

[6]  Holger Hermanns,et al.  Towards Performance Prediction of Compositional Models in Industrial GALS Designs , 2009, CAV.

[7]  Lijun Zhang,et al.  The Quest for Minimal Quotients for Probabilistic Automata , 2013, TACAS.

[8]  Sheldon H. Jacobson,et al.  An algorithm to solve the proportional network flow problem , 2014, Optim. Lett..

[9]  L. Khachiyan Polynomial algorithms in linear programming , 1980 .

[10]  S. Smale,et al.  On a theory of computation and complexity over the real numbers; np-completeness , 1989 .

[11]  Moshe Y. Vardi Automatic verification of probabilistic concurrent finite state programs , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[12]  R. Shamir The Efficiency of the Simplex Method: A Survey , 1987 .

[13]  Cyrus Derman,et al.  Finite State Markovian Decision Processes , 1970 .

[14]  Kurt M. Anstreicher,et al.  Linear Programming in O([n3/ln n]L) Operations , 1999, SIAM J. Optim..

[15]  V. Klee,et al.  HOW GOOD IS THE SIMPLEX ALGORITHM , 1970 .

[16]  Joost-Pieter Katoen,et al.  Automated compositional Markov chain generation for a plain-old telephone system , 2000, Sci. Comput. Program..

[17]  Holger Hermanns,et al.  Deciding Probabilistic Automata Weak Bisimulation in Polynomial Time , 2012, FSTTCS.

[18]  Roberto Segala,et al.  Decision Algorithms for Probabilistic Bisimulation , 2002, CONCUR.

[19]  Lijun Zhang,et al.  On Probabilistic Automata in Continuous Time , 2010, 2010 25th Annual IEEE Symposium on Logic in Computer Science.

[20]  Orhan Feyzioglu,et al.  A network simplex based algorithm for the minimum cost proportional flow problem with disconnected subnetworks , 2012, Optim. Lett..

[21]  Kim Guldstrand Larsen,et al.  Specification and refinement of probabilistic processes , 1991, [1991] Proceedings Sixth Annual IEEE Symposium on Logic in Computer Science.

[22]  Narendra Karmarkar,et al.  A new polynomial-time algorithm for linear programming , 1984, STOC '84.

[23]  Lijun Zhang,et al.  Concurrency and Composition in a Stochastic World , 2010, CONCUR.

[24]  Nadia Tawbi,et al.  Specification and Verification of the PowerScale , 2022 .

[25]  Hans A. Hansson Time and probability in formal design of distributed systems , 1991, DoCS.

[26]  Sheldon H. Jacobson,et al.  A Network Simplex Algorithm for the Equal Flow Problem on a Generalized Network , 2013, INFORMS J. Comput..

[27]  David K. Smith Network Flows: Theory, Algorithms, and Applications , 1994 .

[28]  Andrew Hinton,et al.  PRISM: A Tool for Automatic Verification of Probabilistic Systems , 2006, TACAS.

[29]  Herminia I. Calvete Network simplex algorithm for the general equal flow problem , 2003, Eur. J. Oper. Res..

[30]  Ilan Adler,et al.  A Strongly Polynomial Algorithm for a Special Class of Linear Programs , 1991, Oper. Res..

[31]  R. Helgason,et al.  Chapter 2 Primal simplex algorithms for minimum cost network flows , 1995 .

[32]  Bernd Becker,et al.  Compositional Dependability Evaluation for STATEMATE , 2009, IEEE Transactions on Software Engineering.

[33]  Roberto Segala,et al.  Modeling and verification of randomized distributed real-time systems , 1996 .

[34]  Insup Lee,et al.  Weak Bisimulation for Probabilistic Systems , 2000, CONCUR.

[35]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.