Deterministic Transition Systems Research Articles

Lowerbounds for Bisimulation by Partition Refinement

We provide time lower bounds for sequential and parallel algorithms deciding bisimulation on labeled transition systems that use partition refinement. For sequential algorithms this is $\Omega((m \mkern1mu {+} \mkern1mu n ) \mkern-1mu \log \mkern-1mu n)$ and for parallel algorithms this is $\Omega(n)$, where $n$ is the number of states and $m$ is the number of transitions. The lowerbounds are obtained by analysing families of deterministic transition systems, ultimately with two actions in the sequential case, and one action for parallel algorithms. For deterministic transition systems with one action, bisimilarity can be decided sequentially with fundamentally different techniques than partition refinement. In particular, Paige, Tarjan, and Bonic give a linear algorithm for this specific situation. We show, exploiting the concept of an oracle, that this approach is not of help to develop a faster generic algorithm for deciding bisimilarity. For parallel algorithms there is a similar situation where these techniques may be applied, too.

Cost Partitioning Heuristics for Stochastic Shortest Path Problems

In classical planning, cost partitioning is a powerful method which allows to combine multiple admissible heuristics while retaining an admissible bound. In this paper, we extend the theory of cost partitioning to probabilistic planning by generalizing from deterministic transition systems to stochastic shortest path problems (SSPs). We show that fundamental results related to cost partitioning still hold in our extended theory. We also investigate how to optimally partition costs for a large class of abstraction heuristics for SSPs. Lastly, we analyze occupation measure heuristics for SSPs as well as the theory of approximate linear programming for reward-oriented Markov decision processes. All of these fit our framework and can be seen as cost-partitioned heuristics.

Optimal Temporal Logic Control for Deterministic Transition Systems With Probabilistic Penalties

We consider an optimal control problem for a weighted deterministic transition system required to satisfy a constraint expressed as a linear temporal logic (LTL) formula over its labels. By assuming that the executions of the system incur time-varying penalties modeled as Markov chains, our goal is to minimize the expected average cumulative penalty incurred between consecutive satisfactions of a desired property. Using concepts from theoretical computer science, we provide two solutions to this problem. First, we derive a provably correct optimal strategy within the class of strategies that do not exploit values of penalties sensed in real time. Second, we show that by taking advantage of locally sensing the penalties, we can construct heuristic strategies leading to lower collected penalty. While still ensuring satisfaction of the LTL constraint, we cannot guarantee optimality in the latter case. We provide a user-friendly implementation of the proposed algorithms and analysis of two case studies.

Incremental controller synthesis in probabilistic environments with temporal logic constraints

In this paper, we consider automatic computation of optimal control strategies for a robot interacting with a set of independent uncontrollable agents in a graph-like environment. The mission specification is given as a syntactically co-safe Linear Temporal Logic formula over some properties that hold at the vertices of the environment. The robot is assumed to be a deterministic transition system, while the agents are probabilistic Markov models. The goal is to control the robot such that the probability of satisfying the mission specification is maximized. We propose a computationally efficient incremental algorithm based on the fact that temporal logic verification is computationally cheaper than synthesis. We present several case studies where we compare our approach to the classical non-incremental approach in terms of computation time and memory usage.

Coalgebras for Fuzzy Transition Systems

This paper studies a coalgebraic theory of fuzzy transition systems. Main conclusions include: the functor FA for deterministic fuzzy transition systems and the functor (P∘F)A for nondeterministic fuzzy transition systems preserve weak pullbacks, and the functor FA has a final coalgebra under some restricted conditions. Moreover, we show how to get a concrete (fuzzy) bisimulation from a coalgebraic bisimulation.

Model checking transactional memories

Model checking transactional memories (TMs) is difficult because of the unbounded number, length, and delay of concurrent transactions, as well as the unbounded size of the memory. We show that, under certain conditions satisfied by most TMs we know of, the model checking problem can be reduced to a finite-state problem, and we illustrate the use of the method by proving the correctness of several TMs, including two-phase locking, DSTM, and TL2. The safety properties we consider include strict serializability and opacity; the liveness properties include obstruction freedom, livelock freedom, and wait freedom. Our main contribution lies in the structure of the proofs, which are largely automated and not restricted to the TMs mentioned above. In a first step we show that every TM that enjoys certain structural properties either violates a requirement on some program with two threads and two shared variables, or satisfies the requirement on all programs. In the second step, we use a model checker to prove the requirement for the TM applied to a most general program with two threads and two variables. In the safety case, the model checker checks language inclusion between two finite-state transition systems, a nondeterministic transition system representing the given TM applied to a most general program, and a deterministic transition system representing a most liberal safe TM applied to the same program. The given TM transition system is nondeterministic because a TM can be used with different contention managers, which resolve conflicts differently. In the liveness case, the model checker analyzes fairness conditions on the given TM transition system.

Linear and Branching System Metrics

We extend the classical system relations of trace inclusion, trace equivalence, simulation, and bisimulation to a quantitative setting in which propositions are interpreted not as boolean values, but as elements of arbitrary metric spaces. Trace inclusion and equivalence give rise to asymmetrical and symmetrical linear distances, while simulation and bisimulation give rise to asymmetrical and symmetrical branching distances. We study the relationships among these distances and we provide a full logical characterization of the distances in terms of quantitative versions of LTL and mu-calculus. We show that, while trace inclusion (respectively, equivalence) coincides with simulation (respectively, bisimulation) for deterministic boolean transition systems, linear and branching distances do not coincide for deterministic metric transition systems. Finally, we provide algorithms for computing the distances over finite systems, together with a matching lower complexity bound.

Labelled State Transition Systems

Labelled State Transition SystemsThis article introduces labelled state transition systems, where transitions may be labelled by words from a given alphabet. Reduction relations from [4] are used to define transitions between states, acceptance of words, and reachable states. Deterministic transition systems are also defined.

AUTOMATIC SERVICE COMPOSITION VIA SIMULATION

In this paper we study the issue of service composition, for services that export a representation of their behavior in the form of a finite deterministic transition system. In particular, given a specification of the target service requested by the client as a finite deterministic transition system, the problem we face is how we can exploit the computations of the available services for realizing the computations of the target service. While ways to tackle such a problem are known, in this paper we present a new technique that is based on the notion of simulation, which is still optimal from the computational complexity point. Notably, such a technique, opens up the possibility of devising composition in a "just-in-time" fashion. Indeed, we show that, by exploiting simulation, it is actually possible to implicitly compute all possible compositions at once, and delay the choice of the actual composition to run-time.

Discrete state estimators for systems on a lattice

We address the problem of estimating discrete variables in a class of deterministic transition systems in which the continuous variables are available for measurement. We propose a novel approach to the estimation of discrete variables using lattice theory that overcomes some of the severe complexity issues encountered in previous work. The methodology proposed for the estimation of discrete variables is general as it is applicable to any observable system. Extensions generalize the approach to nondeterministic transition systems. The proposed estimator is finally constructed for a multi-robot system involving two teams competing against each other.

Abstract interpretation of programs as Markov decision processes

We propose a formal language for the specification of trace properties of probabilistic, nondeterministic transition systems, encompassing the properties expressible in Linear Time Logic. Those formulas are in general undecidable on infinite deterministic transition systems and thus on infinite Markov decision processes. This language has both a semantics in terms of sets of traces, as well as another semantics in terms of measurable functions; we give and prove theorems linking the two semantics. We then apply abstract interpretation-based techniques to give upper bounds on the worst-case probability of the studied property. We propose an enhancement of this technique when the state space is partitioned — for instance along the program points — allowing the use of faster iteration methods.

Games for synthesis of controllers with partial observation

The synthesis of controllers for discrete event systems, as introduced by Ramadge and Wonham, amounts to computing winning strategies in parity games. We show that in this framework it is possible to extend the specifications of the supervised systems as well as the constraints on the controllers by expressing them in the modal μ-calculus. In order to express unobservability constraints, we propose an extension of the modal μ-calculus in which one can specify whether an edge of a graph is a loop. This extended μ-calculus still has the interesting properties of the classical one. In particular it is equivalent to automata with loop testing. The problems such as emptiness testing and elimination of alternation are solvable for such automata. The method proposed in this paper to solve a control problem consists in transforming this problem into a problem of satisfiability of a μ-calculus formula so that the set of models of this formula is exactly the set of controllers that solve the problem. This transformation relies on a simple construction of the quotient of automata with loop testing by a deterministic transition system. This is enough to deal with centralized control problems. The solution of decentralized control problems uses a more involved construction of the quotient of two automata. This work extends the framework of Ramadge and Wonham in two directions. We consider infinite behaviours and arbitrary regular specifications, while the standard framework deals only with specifications on the set of finite paths of processes. We also allow dynamic changes of the sets of observable and controllable events.