Combining constraints using logical connectives such as disjunction is ubiquitous in constraint programming, because it adds considerable expressive power to a constraint language...
Christopher Jefferson, Neil C. A. Moore, Peter Nig...
Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has...
In constraint programming one models a problem by stating constraints on acceptable solutions. The constraint model is then usually solved by interleaving backtracking search and ...
The integration of methods of Constraint Programming and Multi-Agent-Systems is discussed in this paper. We describe different agent topologies for Constraint Satisfaction Problem...
This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routi...
Constraint programming is a commonly used technology for solving complex combinatorial problems. However, users of this technology need significant expertise in order to model the...
Machine learning and data mining have become aware that using constraints when learning patterns and rules can be very useful. To this end, a large number of special purpose syste...
Abstract. The stochastic satisfiability modulo theories (SSMT) problem is a generalization of the SMT problem on existential and randomized (aka. stochastic) quantification over di...
Abstract. Call control features (e.g., call-divert, voice-mail) are primitive options to which users can subscribe off-line to personalise their service. The configuration of a fea...
David Lesaint, Deepak Mehta, Barry O'Sullivan, Lui...
The Cell BE processor provides both scalable computation power and flexibility, and it is already being adopted for many computational intensive applications like aerospace, defens...