Gist: a solver for probabilistic games

Authors:
Krishnendu Chatterjee;Thomas A. Henzinger;Barbara Jobstmann;Arjun Radhakrishna
Affiliations:
IST Austria (Institute of Science and Technology Austria);IST Austria (Institute of Science and Technology Austria);CNRS/Verimag, France;IST Austria (Institute of Science and Technology Austria)
Venue:
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Year:
2010

Citing 5
Cited 3

Trees, automata, and games

STOC '82 Proceedings of the fourteenth annual ACM symposium on Theory of computing
Quantitative stochastic parity games

SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Environment Assumptions for Synthesis

CONCUR '08 Proceedings of the 19th international conference on Concurrency Theory
Stochastic o-regular games

Stochastic o-regular games
GOAL extended: towards a research tool for omega automata and temporal logic

TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems

Automatic verification of competitive stochastic systems

TACAS'12 Proceedings of the 18th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Towards communication-based steering of complex distributed systems

Proceedings of the 17th Monterey conference on Large-Scale Complex IT Systems: development, operation and management
PRISM-games: a model checker for stochastic multi-player games

TACAS'13 Proceedings of the 19th international conference on Tools and Algorithms for the Construction and Analysis of Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Gist is a tool that (a) solves the qualitative analysis problem of turn-based probabilistic games with ω-regular objectives; and (b) synthesizes reasonable environment assumptions for synthesis of unrealizable specifications Our tool provides the first and efficient implementations of several reduction-based techniques to solve turn-based probabilistic games, and uses the analysis of turn-based probabilistic games for synthesizing environment assumptions for unrealizable specifications.