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An Operational Semantics for Probabilistic Concurrent Constraint Programming
, 1998
"... This paper investigates a probabilistic version of the concurrent constraint programming paradigm (CCP). The aim is to introduce the possibility to formulate so called "randomised algorithms" within the CCP framework. Differently from common approaches in (imperative) highlevel programmin ..."
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Cited by 32 (12 self)
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This paper investigates a probabilistic version of the concurrent constraint programming paradigm (CCP). The aim is to introduce the possibility to formulate so called "randomised algorithms" within the CCP framework. Differently from common approaches in (imperative) highlevel programming languages, which rely on some kind of random() function, we introduce randomness in the very definition of the language by means of a probabilistic choice construct. This allows a program to make stochastic moves during its execution. We call the resulting language Probabilistic Concurrent Constraint Programming (PCCP). We present an operational semantics for PCCP by means of a probabilistic transition system such that the execution of a PCCP program may be seen as a stochastic process, i.e. as a random walk on the transition graph. The transition probabilities are given explicitly. This semantics captures a notion of observables which combines results of computations and the probability of those re...
Randomised Algorithms and Constraint Logic Programming
 IN JICSLP'98 { JOINT INTERNATIONAL CONFERENCE AND SYMPOSIUM ON LOGIC PROGRAMMING
, 1998
"... We propose a declarativebased implementation of randomised algorithms, which exploits the Constraint Logic Programming (CLP) paradigm. For the highlevel formalisation of probabilistic programs expressing such algorithms we actually refer to a generalisation of CLP, namely the Probabilistic Concurr ..."
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Cited by 5 (2 self)
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We propose a declarativebased implementation of randomised algorithms, which exploits the Constraint Logic Programming (CLP) paradigm. For the highlevel formalisation of probabilistic programs expressing such algorithms we actually refer to a generalisation of CLP, namely the Probabilistic Concurrent Constraint Programming (PCCP) language, previously introduced in [DW97]. This language provides a construct for probabilistic choice which allows us to express randomness in a program. PCCP also includes synchronisation and concurrency aspects. However, for the purpose of this work, the (probabilistic) CLP fragment of PCCP is sufficient. We present a metainterpreter for this language. This is just a standard prolog metainterpreter, suitably extended so as to deal with probabilistic choice. For the constraint solving, the metainterpreter exploits existing constraint handling facilities (and in more concrete terms to the SICStus 3.#6 system). This is possible because the design of PCCP d...
A distriuted and probabilistic concurrent constraint programming language
, 2005
"... Abstract. We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (pr ..."
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Cited by 2 (1 self)
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Abstract. We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (probabilistic) CCP, the communications among different nodes are synchronous. There are channels, and through them different objects can be exchanged: constraints, agents and channel themselves. In addition, all this activities are embedded in a probabilistic scheme based on a discrete model of time, both locally and globally. Finally we enhance the language with the capability of performing an automatic remote synchronization of variables belonging to different constraint stores. 1
Abstract Stochastic Concurrent Constraint Programming
"... associate a rate to each basic instruction that interacts with the constraint store. We give an operational semantic that can be provided either with a discrete or a continuous model of time. The notion of observables is discussed, both for the discrete and the continuous version, and a connection b ..."
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associate a rate to each basic instruction that interacts with the constraint store. We give an operational semantic that can be provided either with a discrete or a continuous model of time. The notion of observables is discussed, both for the discrete and the continuous version, and a connection between the two is given.
Quantitative Observables, Averages and Constraint Programming
, 1999
"... We investigate notions of observable behaviour of programs which include quantitative aspects of computation along with the most commonly assumed qualitative ones. We model these notions by means of a transition system where transitions occur with a given probability and an associated `cost' ..."
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We investigate notions of observable behaviour of programs which include quantitative aspects of computation along with the most commonly assumed qualitative ones. We model these notions by means of a transition system where transitions occur with a given probability and an associated `cost' expressing some complexity measure (e.g. running time or, in general, resource consumption). The addition of these quantities allows for a natural formulation of the average behaviour of a program, whose specication and analysis is particularly important in the study of system performance and reliability. We base our model on the Concurrent Constraint Programming (CCP) paradigm and we argue that it can be an appropriate base for further developments oriented to the analysis and verication of average properties. 1 Introduction The analysis and verication of a system has a fundamental importance for the system development. The advantages of formal methods for these tasks are well known....
Ergodic Average in Constraint Programming (Extended Abstract)
, 1999
"... ) Alessandra Di Pierro dipierro@di.unipi.it Dipartimento di Informatica, Universita di Pisa, Italy Herbert Wiklicky h.wiklicky@doc.ic.ac.uk Department of Computing, Imperial College, London, UK July 22, 1999 1 Introduction We will discuss the problem of modelling probabilistic properties of constra ..."
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) Alessandra Di Pierro dipierro@di.unipi.it Dipartimento di Informatica, Universita di Pisa, Italy Herbert Wiklicky h.wiklicky@doc.ic.ac.uk Department of Computing, Imperial College, London, UK July 22, 1999 1 Introduction We will discuss the problem of modelling probabilistic properties of constraint programs, which express the average of some quantities of interest. A random variable on the set of constraints is used for assigning to each constraint a real value representing the `cost' of that constraint. This way, we obtain a notion of quantitative observables Q which, although interesting in itself can be used in order to dene dierent types of average properties. One, E(Q) refers to the average over dierent runs of a probabilistic programs and corresponds to the expected value of the random variable. Another one, A(Q), considers the average value of the quantity along the same (innite) program run. In this work we concentrate on the second type of properties, which are also ...