Precise fixpoint computation through strategy iteration

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4421 LNCS, Issue , 2007, Pages 300-315

  Gawlitza, Thomas ^a   Seidl, Helmut ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; INTEGER PROGRAMMING; NUMERICAL METHODS; PROBLEM SOLVING;

FIXPOINT COMPUTATION; INTERVAL EQUATIONS; POSITIVE CONSTANTS; STRATEGY ITERATION;

ITERATIVE METHODS;

EID: 37149029514     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71316-6_21     Document Type: Conference Paper

References (18)

1. H. Bjorklund, S. Sandberg, and S. Vorobyov. Complexity of Model Checking by Iterative Improvement: the Pseudo-Boolean Framework . In Proc. 5th Int. Andrei Ershov Memorial Conf. Perspectives of System Informatics, pages 381-394. LNCS 2890, Springer, 2003.
2. J. Cochet-Terrasson, S. Gaubert, and J. Gunawardena. A Constructive Fixed Point Theorem for Min-Max Functions. Dynamics and Stability of Systems, 14(4): 407-433, 1999.
3. A. Costan, S. Gaubert, E. Goubault, M. Martel, and S. Putot. A Policy Iteration Algorithm for Computing Fixed Points in Static Analysis of Programs. In Computer Aided Verification, 17th Int. Conf. (CAV), pages 462-475. LNCS 3576, Springer Verlag, 2005.
4. P. Cousot and R. Cousot. Static Determination of Dynamic Properties of Programs. In Second Int. Symp. on Programming, pages 106-130. Dunod, Paris, France, 1976.
5. P. Cousot and R. Cousot. Comparison of the Galois Connection and Widening/Narrowing Approaches to Abstract Interpretation. ITASPEFL '91, Bordeaux. BIGRE, 74:107-110, Oct. 1991.
6. T. Gawlitza, I. Reineke, H. Seidl, and R. Wilhelm. Polynomial Exact Interval Analysis Revisited. Technical report, TU München, 2006.
7. A. Hoffman and R. Karp. On Nonterminating Stochastic Games. Management Sci, 12:359-370, 1966.
8. R. Howard. Dynamic Programming and Markov Processes. Wiley, New York, 1960.
9. D. E. Knuth. A Generalization of Dijkstra's algorithm. Information Processing Letters (IPL), 6(1):1-5, 1977.
10. N. Megiddo. On the Complexity of Linear Programming. In T. Bewley, editor, Advances in Economic Theory: 5th World Congress, pages 225-268. Cambridge University Press, 1987.
11. A. Miné. Relational Abstract Domains for the Detection of Floating-Point Run-Time Errors. In European Symposium on Programming (ESOP), volume 2986 of LNCS, pages 3-17. Springer, 2004.
12. A. Miné. Symbolic Methods to Enhance the Precision of Numerical Abstract Domains. In Verification, Model Checking, and Abstract Interpretation, 7th Int. Conf. (VMCAI), pages 348-363. LNCS 3855, Springer Verlag, 2006.
13. A. Puri. Theory of Hybrid and Discrete Systems. PhD thesis, University of California, Berkeley, 1995.
14. M. L. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
15. H. Seidl. Least and Greatest Solutions of Equations over N. Nordic Journal of Computing (NJC), 3(1):41-62, 1996.
16. Z. Su and D. Wagner. A Class of Polynomially Solvable Range Constraints for Interval Analysis Without Widenings. Theor. Comput. Sci (TCS), 345(1):122-138, 2005.
17. I. Vöge and M. Jurdzinski. A Discrete Strategy Improvement Algorithm for Solving Parity Games. In Computer Aided Verification, 12th Int. Conf. (CAV), pages 202-215. LNCS 1855, Springer, 2000.
18. U. Zwick and M. Paterson. The Complexity of Mean Payoff Games on Graphs. Theoretical Computer Science (TCS), 158(1&2):343-359, 1996.