Personalisation and context-awareness are fundamental concerns in Telephony. this paper introduces a rule-based system - 4CRULES - which enables context-sensitive call control by the means of feature configuration rul...
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ISBN:
(纸本)9783642153952
Personalisation and context-awareness are fundamental concerns in Telephony. this paper introduces a rule-based system - 4CRULES - which enables context-sensitive call control by the means of feature configuration rules. 4CRULES is interoperable with standard context services and compositional feature architectures. It has been designed to resolve feature interactions, manage conflicting preferences, and mitigate the uncertainty affecting context data. this is achieved through a constraint optimisation model that maximises adherence to user requirements and domain constraints. Experiments on a suite of instances confirm the practicality of the approach and highlight performance- and adherence-critical factors.
Table constraints play an important role within constraintprogramming. Recently, many schemes or algorithms have been proposed to propagate table constraints or/and to compress their representation. We show that simp...
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ISBN:
(纸本)9783540859574
Table constraints play an important role within constraintprogramming. Recently, many schemes or algorithms have been proposed to propagate table constraints or/and to compress their representation. We show that simple tabular reduction (STR), a technique proposed by J. Ullmann to dynamically maintain the tables of Supports, is very often the most efficient practical approach to enforce generalized arc consistency within MAC. We also describe an optimization of STR which allows limiting the number of operations related to validity checking or search of supports. Interestingly enough, this optimization makes STIR potentially r times faster where r is the arity of the constraint(s). the results of an extensive experimentation that we have conducted with respect to random and structured instances indicate that the optimized algorithm we propose is usually around twice as fast its the original STR and can be up to one order of magnitude faster than previous state-of-the-art algorithms on some series of instances.
Routing problems appear in many practical applications. In the context of constraintprogramming, circuit constraints have been successfully developed to handle problems like the well-known Traveling Salesman Problem ...
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ISBN:
(数字)9783319983349
ISBN:
(纸本)9783319983349;9783319983332
Routing problems appear in many practical applications. In the context of constraintprogramming, circuit constraints have been successfully developed to handle problems like the well-known Traveling Salesman Problem or the Vehicle Routing Problem. these kind of constraints are linked to the search for a Hamiltonian circuit in a graph. In this paper we consider a more general multiple tour problem that consists in covering a part of the graph with a set of minimal cost circuits. We define a new global constraint WEIGHTEDSUBCIRCUITS that generalizes the WeightedCircuit constraint by releasing the need to obtain a Hamiltonian circuit. It enforces multiple disjoint circuits of bounded total cost to partially cover a weighted graph, the subsets of vertices to be covered being induced by external constraints. We show that enforcing Bounds Consistency for WeightedSubCircuits is NP-hard. We propose an incomplete but polynomial filtering method based on the search for a lower bound of a weighted Steiner circuit.
the Still-Life problem is challenging for cp techniques because the basic constraints of the game of Life are loose and give poor propagation for Still-Life. In this paper, we show how ad hoc global case constraints c...
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the Still-Life problem is challenging for cp techniques because the basic constraints of the game of Life are loose and give poor propagation for Still-Life. In this paper, we show how ad hoc global case constraints can be customized to construct various models to provide much stronger propagation withcp solvers. Since we use custom ad hoc constraints of high arity where the number of tuples to define the constraint are large, the actual constraint representation becomes important to avoid excessive space consumption. We demonstrate how to use BDDs to construct good representations for the case constraint which is critical for efficiency. Our results seem comparable to hybrid cp/IP models even though we are only using propagation albeit on ad hoc global constraints. this paper shows an extensive example of how to systematically build models using different kinds of ad hoc constraints. It also demonstrates the solving potential of ad hoc global constraints.
the class of constraint satisfaction problems (CSPs) over finite domains has been shown to be NP-complete, but many tractable subclasses have been identified in the literature. In this paper we are interested in restr...
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ISBN:
(纸本)3540666265
the class of constraint satisfaction problems (CSPs) over finite domains has been shown to be NP-complete, but many tractable subclasses have been identified in the literature. In this paper we are interested in restrictions on the types of constraint relations in CSP instances. By a result of Jeavons et al. we know that a key to the complexity of classes arising from such restrictions is the closure properties of the sets of relations. It has been shown that sets of relations that are closed under constant, majority, affine, or associative, commutative, and idempotent (ACI) functions yield tractable subclasses of CSP. However, it has been unknown whether other closure properties may generate tractable subclasses. In this paper we introduce a class of tractable (in fact, SL-complete) CSPs based on bipartite graphs. We show that there are members of this class that are not closed under constant, majority, affine, or ACI functions, and that it, therefore, is incomparable with previously identified classes.
Today many companies face the challenge of matching highly-skilled professionals to high-end positions in large organizations and human deployment agencies. Non-accurate matches in these businesses can result in signi...
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ISBN:
(纸本)9783642153952
Today many companies face the challenge of matching highly-skilled professionals to high-end positions in large organizations and human deployment agencies. Non-accurate matches in these businesses can result in significant monetary losses and other negative effects. Unlike traditional Workforce Management (WM) problems such as shift scheduling, highly-skilled employees are professionally distinguishable from each other and hence non-interchangeable. therefore, the techniques used for shift-scheduling can't be applied to the highly-skilled WM domain. Our work focuses on providing a constraintprogramming solution for supporting the assignment of highly-skilled professionals. Our experience shows that cp is well adapted to this problem. cp supports very well the underlying constraints. In addition, the rich expressive language supported by cp allows us to provide a convenient mechanism for changing and adding new matching and preference constraints. Based on this technology, we have built a tool that is currently being used by IBM service organizations and provides strong business results.
In this paper, we propose a new language-independent representation of adhoc constraints, called a box constraint collection. Using constructive disjunction, this representation achieves domain consistency. We develop...
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the automatic tuning of the parameters of algorithms and automatic selection of algorithms has received a lot of attention recently. One possible approach is the use of machine learning techniques to learn classifiers...
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ISBN:
(纸本)9783642153952
the automatic tuning of the parameters of algorithms and automatic selection of algorithms has received a lot of attention recently. One possible approach is the use of machine learning techniques to learn classifiers which, given the characteristics of a particular problem, make a decision as to which algorithm or what parameters to use. Little research has been done into which machine learning algorithms are suitable and the impact of picking the "right" over the "wrong" technique. this paper investigates the differences in performance of several techniques on different data sets. it furthermore provides evidence that by using a meta-technique which combines several machine learning algorithms, we can avoid the problem of having to pick the "best" one and still achieve good performance.
We present a general constraint-based encoding for domain-independent task planning. Task planning is characterized by causal relationships expressed as conditions and effects of optional actions. Possible actions are...
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ISBN:
(数字)9783319983349
ISBN:
(纸本)9783319983349;9783319983332
We present a general constraint-based encoding for domain-independent task planning. Task planning is characterized by causal relationships expressed as conditions and effects of optional actions. Possible actions are typically represented by templates, where each template can be instantiated into a number of primitive actions. While most previous work for domain-independent task planning has focused on primitive actions in a state-oriented view, our encoding uses a fully lifted representation at the level of action templates. It follows a time-oriented view in the spirit of previous work in constraint-based scheduling. As a result, the proposed encoding is simple and compact as it grows withthe number of actions in a solution plan rather than the number of possible primitive actions. When solved with an SMT solver, we show that the proposed encoding is slightly more efficient than state-of-the-art methods on temporally constrained planning benchmarks while clearly outperforming other fully constraint-based approaches.
We present a new complete multi-valued SAT solver, based on current state-of-the-art SAT technology. It features watched literal propagation and conflict driven clause learning. We combine this technology with state-o...
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ISBN:
(纸本)9783642153952
We present a new complete multi-valued SAT solver, based on current state-of-the-art SAT technology. It features watched literal propagation and conflict driven clause learning. We combine this technology with state-of-the-art cp methods for branching and introduce quantitative supports which augment the watched literal scheme with a watched domain size scheme. Most importantly, we adapt SAT nogood learning for the multi-valued case and demonstrate that exploiting the knowledge that each variable must take exactly one out of many values can lead to much stronger nogoods. Experimental results assess the benefits of these contributions and show that solving multi-valued SAT directly often works better than reducing multi-valued constraint problems to SAT.
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