On probabilistic timed automata

  • Authors:
  • Danièle Beauquier

  • Affiliations:
  • Department of Informatics, University Paris-12, 61 Av. du Gén. de Gaulle, 94010, Créteil, France

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2003

Quantified Score

Hi-index 5.23

Visualization

Abstract

We propose a model of probabilistic timed automaton which substitutes for the nondeterminism of an ordinary timed automaton, a new one (directly drawn from Markov decision processes) by means of actions which provide a probabilistic distribution over transitions. Using Büchi acceptance conditions, timed automata can refer timing properties as "during every open time interval of length 1 at least one message is delivered". A policy is a mechanism which solves the non-determinism by choosing for each finite run an action and the time moment of the next transition step implied by this action. We prove that, given a probabilistic timed automaton A, there exists a Markov (memoryless) policy which maximizes the probability p of the set of accepting runs realized by this policy. This policy as well as the maximal value of p are computable in polytime in the size of the region automaton of A. This result provides an algorithm of model-checking for properties like "there is a policy which realizes a correct behavior of the system with probability at least p".