Results 1 - 10 of 60,500

Symbolic Methods for Exploring Infinite State Spaces

by Bernard Boigelot , 1998
"... In this thesis, we introduce a general method for computing the set of reachable states of an infinite-state system. The basic idea, inspired by well-known statespace exploration methods for finite-state systems, is to propagate reachability from the initial state of the system in order to determine ..."
Abstract - Cited by 72 (9 self) - Add to MetaCart
-transition, which is a mathematical object that can be associated to the model, and whose purpose is to make it possible to compute in a finite amount of time an infinite set of reachable states. Different methods for creating meta-transitions are studied. We also study the properties that can be verified by state-space

Metrics for Markov Decision Processes with Infinite State Spaces

by Norm Ferns, et al. , 2005
"... We present metrics for measuring state similarity in Markov decision processes (MDPs) with infinitely many states, including MDPs with continuous state spaces. Such metrics provide a stable quantitative analogue of the notion of bisimulation for MDPs, and are suitable for use in MDP approximation. W ..."
Abstract - Cited by 15 (4 self) - Add to MetaCart
We present metrics for measuring state similarity in Markov decision processes (MDPs) with infinitely many states, including MDPs with continuous state spaces. Such metrics provide a stable quantitative analogue of the notion of bisimulation for MDPs, and are suitable for use in MDP approximation

Liveness Checking as Safety Checking for Infinite State Spaces

by Viktor Schuppan, Armin Biere , 2005
"... In previous work we have developed a syntactic reduction of repeated reachability to reachability for finite state systems. This may lead to simpler and more uniform proofs for model checking of liveness properties, help to find shortest counterexamples, and overcome limitations of closed-source mod ..."
Abstract - Cited by 6 (1 self) - Add to MetaCart
-source model-checking tools. In this paper we show that a similar reduction can be applied to a number of infinite state systems, namely, (#-)regular model checking, push-down systems, and timed automata.

Coordinated Learning in Multiagent MDPs with Infinite State-Space

by Francisco S Melo, M. Isabel Ribeiro
"... ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract not found

Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis

by Theodore J. Perkins, Andrew G. Barto - Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence , 2001
"... In infinite state spaces, many standard heuristic search algorithms do not terminate if the problem is unsolvable. Under some conditions, they can fail to terminate even when there are solutions. We show how techniques from control theory, in particular Lyapunov stability analysis, can be emplo ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
In infinite state spaces, many standard heuristic search algorithms do not terminate if the problem is unsolvable. Under some conditions, they can fail to terminate even when there are solutions. We show how techniques from control theory, in particular Lyapunov stability analysis, can

Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis

by unknown authors
"... In infinite state spaces, many standard heuristic search algorithms do not terminate if the problem is unsolvable. Under some conditions, they can fail to terminate even when there are solutions. We show how techniques from control theory, in particular Lyapunov stability analysis, can be employed t ..."
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In infinite state spaces, many standard heuristic search algorithms do not terminate if the problem is unsolvable. Under some conditions, they can fail to terminate even when there are solutions. We show how techniques from control theory, in particular Lyapunov stability analysis, can be employed

Metrics for Markov Decision Processes with Infinite State Spaces Norm Ferns

by unknown authors
"... We present metrics for measuring state similarity in Markov decision processes (MDPs) with infinitely many states, including MDPs with continuous state spaces. Such metrics provide a stable quantitative analogue of the notion of bisimulation for MDPs, and are suitable for use in MDP approximation. W ..."
Abstract - Add to MetaCart
We present metrics for measuring state similarity in Markov decision processes (MDPs) with infinitely many states, including MDPs with continuous state spaces. Such metrics provide a stable quantitative analogue of the notion of bisimulation for MDPs, and are suitable for use in MDP approximation

Symbolic Verification of Communication Protocols with Infinite State Spaces using QDDs (Extended Abstract)

by Bernard Boigelot, Patrice Godefroid - In CAV'96. LNCS 1102
"... ) Bernard Boigelot Universit'e de Li`ege Institut Montefiore, B28 4000 Li`ege Sart-Tilman, Belgium Email: boigelot@montefiore.ulg.ac.be Patrice Godefroid Lucent Technologies -- Bell Laboratories 1000 E. Warrenville Road Naperville, IL 60566, U.S.A. Email: god@bell-labs.com Abstract We study ..."
Abstract - Cited by 94 (8 self) - Add to MetaCart
communication protocol, even if this state space is infinite. Our algorithm performs a loo...

The algorithmic analysis of hybrid systems

by R. Alur, C. Courcoubetis, N. Halbwachs , T. A. Henzinger, P.-H. Ho, X. Nicollin , A. Olivero , J. Sifakis , S. Yovine - THEORETICAL COMPUTER SCIENCE , 1995
"... We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamica ..."
Abstract - Cited by 778 (71 self) - Add to MetaCart
to linear hybrid systems. In particular, we consider symbolic model-checking and minimization procedures that are based on the reachability analysis of an infinite state space. The procedures iteratively compute state sets that are definable as unions of convex polyhedra in multidimensional real space. We

The Infinite Hidden Markov Model

by Matthew J. Beal, Zoubin Ghahramani, Carl E. Rasmussen - Machine Learning , 2002
"... We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integrate out the infinitely many transition parameters, leaving only three hyperparameters which can be learned from data. Th ..."
Abstract - Cited by 637 (41 self) - Add to MetaCart
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integrate out the infinitely many transition parameters, leaving only three hyperparameters which can be learned from data
Results 1 - 10 of 60,500