15,897 research outputs found
Stochastic Constraint Programming
To model combinatorial decision problems involving uncertainty and
probability, we introduce stochastic constraint programming. Stochastic
constraint programs contain both decision variables (which we can set) and
stochastic variables (which follow a probability distribution). They combine
together the best features of traditional constraint satisfaction, stochastic
integer programming, and stochastic satisfiability. We give a semantics for
stochastic constraint programs, and propose a number of complete algorithms and
approximation procedures. Finally, we discuss a number of extensions of
stochastic constraint programming to relax various assumptions like the
independence between stochastic variables, and compare with other approaches
for decision making under uncertainty.Comment: Proceedings of the 15th Eureopean Conference on Artificial
Intelligenc
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
Finite domain constraint programming systems
Tutorial at CP'2002, Principles and Practice of Constraint Programming. Powerpoint slides.</p
Concurrent constraint programming with process mobility
We propose an extension of concurrent constraint programming with primitives for process migration within a hierarchical network, and we study its semantics. To this purpose, we first investigate a "pure " paradigm for process migration, namely a paradigm where the only actions are those dealing with transmissions of processes. Our goal is to give a structural definition of the semantics of migration; namely, we want to describe the behaviour of the system, during the transmission of a process, in terms of the behaviour of the components. We achieve this goal by using a labeled transition system where the effects of sending a process, and requesting a process, are modeled by symmetric rules (similar to handshaking-rules for synchronous communication) between the two partner nodes in the network. Next, we extend our paradigm with the primitives of concurrent constraint programming, and we show how to enrich the semantics to cope with the notions of environment and constraint store. Finally, we show how the operational semantics can be used to define an interpreter for the basic calculus.
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