Timed Soft Concurrent Constraint Programs

Bistarelli, Stefano; Gabbrielli, Maurizio; Meo, Maria Chiara; Santini, Francesco

doi:10.1007/978-3-540-68265-3_4

Cited by 16 publications

(19 citation statements)

References 18 publications

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“…A timed extension of scc has been proposed in [5] in order to be able to express also Quality of Service aspects which involve time. As in the case of scc, tell and ask agents are equipped with a preference (or consistency) threshold which is used to determine their success or suspension.…”

Section: Ccp For Service Level Agreementmentioning

confidence: 99%

Concurrent and Reactive Constraint Programming

Gabbrielli¹,

Palamidessi²,

Valencia³

2010

Lecture Notes in Computer Science

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Abstract. The Italian Logic Programming community has given several contributions to the theory of Concurrent Constraint Programming. In particular, in the topics of semantics, verification, and timed extensions. In this paper we review the main lines of research and contributions of the community in this field. ([52, 56, 57]) emerged as one of the most successful proposals in this area. Concurrent constraint programming (ccp) presented two new perspectives on the underlying philosophy of logic programming. One is the replacement of the concept of unification over the Herbrand universe by the more general notion of constraint over an arbitrary domain. This is in a sense a 'natural' development, and the idea was already introduced in 'sequential' logic programming by Jaffar and Lassez ([45]). The other is the introduction of extra-logical operators typical of the imperative concurrent paradigms, like CCS ([47]), TCSP ([8]) and ACP ([1]); in particular, the choice (+), the action prefixing (→), and the hiding operator (∃). Additionally, concurrent constraint programming embodies an explicit characterization of the control mechanisms for communication and synchronization by means of the introduction of two kinds of actions (ask and tell). Also in concurrent logic languages these control features were present, but they were hidden in various ways: the choice was represented by alternative clauses, hiding by local (existentially quantified) variables, prefixing by commitment, communication by sharing of variables, and synchronization by restrictions on the unification algorithm.

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Section: Ccp For Service Level Agreementmentioning

confidence: 99%

Concurrent and Reactive Constraint Programming

Gabbrielli¹,

Palamidessi²,

Valencia³

2010

Lecture Notes in Computer Science

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“…Scc programming has been also extended to deal with timed [20] and nonmonotonic [35] issues. The timed extension is based on the hypothesis of bounded asynchrony: computation takes a bounded period of time and is measured by a discrete global clock.…”

Section: Soft CCmentioning

confidence: 99%

Semiring-Based Soft Constraints

Bistarelli

Rossi

2008

Concurrency, Graphs and Models

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Abstract. The semiring-based formalism to model soft constraint has been introduced in 1995 by Ugo Montanari and the authors of this paper. The idea was to make constraint programming more flexible and widely applicable. We also wanted to define the extension via a general formalism, so that all its instances could inherit its properties and be easily compared. Since then, much work has been done to study, extend, and apply this formalism. This papers gives a brief summary of some of these research activities. Before soft constraints: a brief introduction to constraint programmingConstraint programming [1,42,60,74,68] is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The basic idea in constraint programming is that the user states the constraints and a general purpose constraint solver solves them. Constraints are just relations, and a constraint satisfaction problem (CSP) states which relations should hold among the given decision variables. For example, in scheduling activities in a company, the decision variables might be the starting times and the durations of the activities, as well as the resources needed to perform them, and the constraints might be on the availability of the resources and on their use for a limited number of activities at a time.Constraint solvers take a real-world problem, represented in terms of decision variables and constraints, and find an assignment of values to all the variables that satisfies all the constraints. Constraint solvers search the solution space either systematically, as with backtracking or branch and bound algorithms, or use forms of local search which may be incomplete. Systematic methods often interleave search and inference, where inference consists of propagating the

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“…Our intention is also to further extend the SCC language in order to join together the expressive capabilities of soft constraints and timing mechanisms (Bistarelli et al 2008). The agents modeled with this language will be able to deal with time and preference dependent decisions that can often be found during complex interactions as, for example, auctions: the cost for a service or a good can be raised or lowered during the auction process.…”

Section: Current and Future Workmentioning

confidence: 99%