Abstract. We address the inclusion of stochastic information into an explicitly timed concurrent constraint process language. An operational semantics is proposed as a preliminary result. Our approach finds applications in biology, among other areas. Motivation. The study of quantitative information within languages for concurrency has recently gained a lot of momentum. In many applications, quantitative information becomes crucial when refining models with empirical data, and is of the essence for verification purposes. Two main models of quantitative information can be singled out from the vast literature on the subject. Given a computation that can perform different, competing actions, a probabilistic model provides a probability distribution over such actions. In contrast, a stochastic model relates each action to a random variable which determines its duration: given a set of competing actions, the fastest action (i.e. the one with the shortest duration) is executed. Consequently, notions not considered in a probabilistic model (e.g. speed) are fundamental in a stochastic setting. Not surprisingly, areas in which time is essential (e.g. systems biology, performance modeling) have found in languages featuring stochastic information adequate frameworks for analysis. Concurrent constraint programming (CCP) [1] is a declarative model for concurrency with strong ties to logic. In CCP, systems are described by pieces of partial information called constraints. Processes interact in a shared store; they either add new constraints or synchronize on the already available information. Timed concurrent constraint programming (tcc) [2] is a declarative framework for reactive systems. In tcc, time is explicitly represented as discrete time units in which computation takes place; tcc provides constructs to control process execution along such units. In the light of stochastic models for quantitative information, the explicit time in tcc poses a legitimate question, that of determining to what extent the notions of stochastic duration and
J. Aranda et al. REF associate a random variable to each computation for determining its time duration: given a set of competing actions, the fastest action is executed (i.e., the one with the shortest duration).
Stochastic Behavior and Explicit Discrete Time in Concurrent Constraint Programming ?
Computer Science