25,099 research outputs found
A Simulation Tool for tccp Programs
The Timed Concurrent Constraint Language tccp is a declarative synchronous concurrent language, particularly suitable for modelling reactive systems. In tccp, agents communicate and synchronise through a global constraint store. It supports a notion of discrete time that allows all non-blocked agents to proceed with their execution simultaneously.
In this paper, we present a modular architecture for the simulation of tccp programs. The tool comprises three main components. First, a set of basic abstract instructions able to model the tccp agent behaviour, the memory model needed to manage the active agents and the state of the store during the execution. Second, the agent interpreter that executes the instructions of the current agent iteratively and calculates the new agents to be executed at the next time instant. Finally, the constraint solver components which are the modules that deal with constraints.
In this paper, we describe the implementation of these components and present an example of a real system modelled in tccp.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
An Integrated Development Environment for Declarative Multi-Paradigm Programming
In this paper we present CIDER (Curry Integrated Development EnviRonment), an
analysis and programming environment for the declarative multi-paradigm
language Curry. CIDER is a graphical environment to support the development of
Curry programs by providing integrated tools for the analysis and visualization
of programs. CIDER is completely implemented in Curry using libraries for GUI
programming (based on Tcl/Tk) and meta-programming. An important aspect of our
environment is the possible adaptation of the development environment to other
declarative source languages (e.g., Prolog or Haskell) and the extensibility
w.r.t. new analysis methods. To support the latter feature, the lazy evaluation
strategy of the underlying implementation language Curry becomes quite useful.Comment: In A. Kusalik (ed), proceedings of the Eleventh International
Workshop on Logic Programming Environments (WLPE'01), December 1, 2001,
Paphos, Cyprus. cs.PL/011104
Abstract State Machines 1988-1998: Commented ASM Bibliography
An annotated bibliography of papers which deal with or use Abstract State
Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm
Soft Concurrent Constraint Programming
Soft constraints extend classical constraints to represent multiple
consistency levels, and thus provide a way to express preferences, fuzziness,
and uncertainty. While there are many soft constraint solving formalisms, even
distributed ones, by now there seems to be no concurrent programming framework
where soft constraints can be handled. In this paper we show how the classical
concurrent constraint (cc) programming framework can work with soft
constraints, and we also propose an extension of cc languages which can use
soft constraints to prune and direct the search for a solution. We believe that
this new programming paradigm, called soft cc (scc), can be also very useful in
many web-related scenarios. In fact, the language level allows web agents to
express their interaction and negotiation protocols, and also to post their
requests in terms of preferences, and the underlying soft constraint solver can
find an agreement among the agents even if their requests are incompatible.Comment: 25 pages, 4 figures, submitted to the ACM Transactions on
Computational Logic (TOCL), zipped file
Logic programming in the context of multiparadigm programming: the Oz experience
Oz is a multiparadigm language that supports logic programming as one of its
major paradigms. A multiparadigm language is designed to support different
programming paradigms (logic, functional, constraint, object-oriented,
sequential, concurrent, etc.) with equal ease. This article has two goals: to
give a tutorial of logic programming in Oz and to show how logic programming
fits naturally into the wider context of multiparadigm programming. Our
experience shows that there are two classes of problems, which we call
algorithmic and search problems, for which logic programming can help formulate
practical solutions. Algorithmic problems have known efficient algorithms.
Search problems do not have known efficient algorithms but can be solved with
search. The Oz support for logic programming targets these two problem classes
specifically, using the concepts needed for each. This is in contrast to the
Prolog approach, which targets both classes with one set of concepts, which
results in less than optimal support for each class. To explain the essential
difference between algorithmic and search programs, we define the Oz execution
model. This model subsumes both concurrent logic programming
(committed-choice-style) and search-based logic programming (Prolog-style).
Instead of Horn clause syntax, Oz has a simple, fully compositional,
higher-order syntax that accommodates the abilities of the language. We
conclude with lessons learned from this work, a brief history of Oz, and many
entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic
Programming
Analyzing logic programs with dynamic scheduling
Traditional logic programming languages, such as Prolog, use a fixed left-to-right atom scheduling rule. Recent logic programming languages, however, usually provide more flexible scheduling in which computation generally proceeds leftto- right but in which some calis are dynamically
"delayed" until their arguments are sufRciently instantiated
to allow the cali to run efficiently. Such dynamic scheduling has a significant cost. We give a framework for the global analysis of logic programming languages with dynamic scheduling and show that program analysis based on this framework supports optimizations which remove much
of the overhead of dynamic scheduling
- …