A Comparison of Time- and Reward-Bounded Probabilistic Model Checking Techniques

In the design of probabilistic timed systems, requirements concerning behaviour that occurs within a given time or energy budget are of central importance. We observe that model-checking such requirements for probabilistic timed automata can be reduced to checking reward-bounded properties on Markov decision processes. This is traditionally implemented by unfolding the model according to the bound, or by solving a sequence of linear programs. Neither scales well to large models. Using value iteration in place of linear programming achieves scalability but accumulates approximation error. In this paper, we correct the value iteration-based scheme, present two new approaches based on scheduler enumeration and state elimination, and compare the practical performance and scalability of all techniques on a number of case studies from the literature. We show that state elimination can significantly reduce runtime for large models or high bounds

Symbolic Minimum Expected Time Controller Synthesis for Probabilistic Timed Automata

In this paper we consider the problem of computing the minimum expected time to reach a target and the synthesis of the corresponding optimal controller for a probabilistic timed automaton (PTA). Although this problem admits solutions that employ the digital clocks abstraction or statistical model checking, symbolic methods based on zones and priced zones fail due to the difficulty of incorporating probabilistic branching in the context of dense time. We work in a generalisation of the setting introduced by Asarin and Maler for the corresponding problem for timed automata, where simple and nice functions are introduced to ensure finiteness of the dense-time representation. We find restrictions sufficient for value iteration to converge to the minimum expected time on the uncountable Markov decision process representing the semantics of a PTA. We formulate a Bellman operator on the backwards zone graph of a PTA and prove that value iteration using this operator equals that computed over the PTA’s semantics. This enables us to extract an ε-optimal controller from value iteration in the standard way

Simple Priced Timed Games Are Not That Simple

Priced timed games are two-player zero-sum games played on priced timed automata (whose locations and transitions are labeled by weights modeling the costs of spending time in a state and executing an action, respectively). The goals of the players are to minimise and maximise the cost to reach a target location, respectively. We consider priced timed games with one clock and arbitrary (positive and negative) weights and show that, for an important subclass of theirs (the so-called simple priced timed games), one can compute, in exponential time, the optimal values that the players can achieve, with their associated optimal strategies. As side results, we also show that one-clock priced timed games are determined and that we can use our result on simple priced timed games to solve the more general class of so-called reset-acyclic priced timed games (with arbitrary weights and one-clock)

Undecidability of cost-bounded reachability in priced probabilistic timed automata

Contains fulltext : 75615.pdf (publisher's version ) (Closed access)6th Annual Conference, TAMC 2009, 18 mei 200