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The essence of ESSENCE: A constraint language for specifying combinatorial problems
 In Proceedings of the 20th International Joint Conference on Artificial Intelligence
, 2005
"... Abstract. Essence is a new language for specifying combinatorial (decision or optimisation) problems at a high level of abstraction. The key feature enabling this abstraction is the provision of decision variables whose values can be combinatorial objects, such as tuples, sets, multisets, relations, ..."
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Cited by 62 (15 self)
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Abstract. Essence is a new language for specifying combinatorial (decision or optimisation) problems at a high level of abstraction. The key feature enabling this abstraction is the provision of decision variables whose values can be combinatorial objects, such as tuples, sets, multisets, relations, partitions and functions. Essence also allows these combinatorial objects to be nested to arbitrary depth, thus providing, for example, sets of partitions, sets of sets of partitions, and so forth. 1
The rules of constraint modelling
 In Proc. of the Nineteenth Int. Joint Conf. on Artificial Intelligence
, 2005
"... Many and diverse combinatorial problems have been solved successfully using finitedomain constraint programming. However, to apply constraint programming to a particular domain, the problem must first be modelled as a constraint satisfaction or optimisation problem. Since constraints provide a rich ..."
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Cited by 49 (21 self)
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Many and diverse combinatorial problems have been solved successfully using finitedomain constraint programming. However, to apply constraint programming to a particular domain, the problem must first be modelled as a constraint satisfaction or optimisation problem. Since constraints provide a rich language, typically many alternative models exist. Formulating a good model therefore requires a great deal of expertise. This paper describes CONJURE, a system that refines a specification of a problem in the abstract constraint specification language ESSENCE into a set of alternative constraint models. Refinement is compositional: alternative constraint models are generated by composing refinements of the components of the specification. Experimental results demonstrate that CONJURE is able to generate a variety of models for practical problems from their ESSENCE specifications. 1
The design of ESSENCE: a constraint language for specifying combinatorial problems
 In: Proceedings of IJCAI07
, 2007
"... ESSENCE is a new formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics. ESSENCE provides a high level of abstraction, much of which is the consequence of the provision of decision v ..."
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Cited by 41 (2 self)
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ESSENCE is a new formal language for specifying combinatorial problems in a manner similar to natural rigorous specifications that use a mixture of natural language and discrete mathematics. ESSENCE provides a high level of abstraction, much of which is the consequence of the provision of decision variables whose values can be combinatorial objects, such as tuples, sets, multisets, relations, partitions and functions. ESSENCE also allows these combinatorial objects to be nested to arbitrary depth, thus providing, for example, sets of partitions, sets of sets of partitions, and so forth. Therefore, a problem that requires finding a complex combinatorial object can be directly specified by using a decision variable whose type is precisely that combinatorial object. 1
Extensible Automated Constraint Modelling
"... In constraint solving, a critical bottleneck is the formulation of an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of const ..."
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Cited by 5 (4 self)
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In constraint solving, a critical bottleneck is the formulation of an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE. A set of rules is used to refine an abstract specification into a concrete constraint model. We demonstrate that this set of rules is readily extensible to increase the space of possible constraint models CONJURE can produce. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 32 benchmark problems found in the literature.
The automatic generation of redundant representations and channelling constraints
 In Proceedings of the 5th International Workshop on Constraint Modelling and Reformulation
, 2006
"... Abstract. Constraint modelling is the process of encoding a given problem to be solved by constraint satisfaction technology. Automatic modelling systems aim to reduce the number of decisions human modellers must take. To do so, these systems implement common modelling guidelines and techniques. In ..."
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Abstract. Constraint modelling is the process of encoding a given problem to be solved by constraint satisfaction technology. Automatic modelling systems aim to reduce the number of decisions human modellers must take. To do so, these systems implement common modelling guidelines and techniques. In this paper we focus on the automatic addition of redundant information and most importantly the corresponding channelling constraints to synchronise it. We discuss and formalise a systematic method of generation of both elements; redundancy and channelling constraints. We provide in this paper a new insight on this formalisation that aims to clarify and increase previous work on the subject [1]. 1
The Systematic Generation Of Channelled Models In Constraint Satisfaction
"... Key words: constraint modelling, channelling constraints, channels, channelled models, representations, redundant representations, automatic modelling, refinement Solving a problem with finitedomain constraint programming requires generating a model from the informal description of the problem such ..."
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Cited by 2 (0 self)
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Key words: constraint modelling, channelling constraints, channels, channelled models, representations, redundant representations, automatic modelling, refinement Solving a problem with finitedomain constraint programming requires generating a model from the informal description of the problem such that this model can be accepted by a constraint solver. This generation process, called constraint modelling, is considered a hard task due to the number of choices and decisions it includes. Experience of skilled modellers in handcrafting many effective models has allowed identifying numerous patterns. One of these patterns is the addition of redundant information to a model. When this addition takes place, the consistency between all the redundant information needs to be maintained. The special constraints inserted to carry out this consistency maintenance are called channelling constraints (channels) and the models
The systematic generation of channelling constraints
 In: Fourth International Workshop on Modelling and Reformulating Constraint Satisfaction Problems. (2005) 89–101 Held at the 11th International Conference on Principles and Practice of Constraint Programming
, 2005
"... Abstract. The automatic modelling tool Conjure generates CSP models from problem specifications. The generated models may contain several redundant representations of the same specification variable. The consistency between the alternative representations is maintained by imposing channelling constr ..."
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Abstract. The automatic modelling tool Conjure generates CSP models from problem specifications. The generated models may contain several redundant representations of the same specification variable. The consistency between the alternative representations is maintained by imposing channelling constraints. In this paper we present an algorithm that produces correct channelling constraints for the generated models using only the facilities already provided by the Conjure system.
The rules of constraint modelling: An overview
 In Proceedings of the 12th Workshop on Automated Reasoning,2005. Available at http://www.cs.york.ac.uk/aig/ constraints/AutoModel
"... We address a major bottleneck in the use of constraint programming: modelling. Our system CONJURE automatically refines a specification of a problem in our abstract constraint specification language, ESSENCE, into a set of alternative constraint programs, thus automating an important part of the mo ..."
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We address a major bottleneck in the use of constraint programming: modelling. Our system CONJURE automatically refines a specification of a problem in our abstract constraint specification language, ESSENCE, into a set of alternative constraint programs, thus automating an important part of the modelling process and helping to reduce the modelling bottleneck significantly.
Towards the Systematic Generation of Channelling Constraints
"... Abstract. The automatic modelling tool Conjure generates CSP models from problem specifications. The generated models may contain multiple alternative (redundant) representations of the same variable. However, the combined models generated by Conjure do not include the channelling constraints needed ..."
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Abstract. The automatic modelling tool Conjure generates CSP models from problem specifications. The generated models may contain multiple alternative (redundant) representations of the same variable. However, the combined models generated by Conjure do not include the channelling constraints needed to maintain the consistency between the alternative representations. In this paper we show that by using only the tools already provided by the Conjure system we can generate correct channelling constraints. 1
Why �������? Frequently Asked Questions about a New Language for Specifying Combinatorial Problems
"... Abstract. Essence is a new language for specifying combinatorial (decision or optimisation) problems at a high level of abstraction. Since its introduction, a number of misconceptions about the language and its purpose have arisen in the constraint community. This FAQ addresses some of the frequentl ..."
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Abstract. Essence is a new language for specifying combinatorial (decision or optimisation) problems at a high level of abstraction. Since its introduction, a number of misconceptions about the language and its purpose have arisen in the constraint community. This FAQ addresses some of the frequently arising questions and tries clarify some common misconceptions. This document is not intended to serve as an introduction to the Essence language; that is handled elsewhere [6]). Rather, this document is intended to complement such an introduction. Nonetheless, the answer to the first question provides a very brief introduction to the language. What is �������? Essence is a new language for specifying combinatorial (decision or optimisation) problems at a high level of abstraction. Essence is the result of our attempt to design a formal language that enables problem specifications that are similar to rigorous specifications that use a mixture of natural language and discrete mathematics, such as those catalogued by Garey and Johnson [9].