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19
W.C.: On modeling multiagent task scheduling as a distributed constraint optimization problem
 In: IJCAI
"... This paper investigates how to represent and solve multiagent task scheduling as a Distributed Constraint Optimization Problem (DCOP). Recently multiagent researchers have adopted the C TÆMS language as a standard for multiagent task scheduling. We contribute an automated mapping that transforms C T ..."
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Cited by 17 (3 self)
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This paper investigates how to represent and solve multiagent task scheduling as a Distributed Constraint Optimization Problem (DCOP). Recently multiagent researchers have adopted the C TÆMS language as a standard for multiagent task scheduling. We contribute an automated mapping that transforms C TÆMSinto a DCOP. Further, we propose a set of representational compromises for C TÆMS that allow existing distributed algorithms for DCOP to be immediately brought to bear on C TÆMS problems. Next, we demonstrate a key advantage of a constraint based representation is the ability to leverage the representation to do efficient solving. We contribute a set of preprocessing algorithms that leverage existing constraint propagation techniques to do variable domain pruning on the DCOP. We show that these algorithms can result in 96 % reduction in state space size for a given set of C TÆMS problems. Finally, we demonstrate up to a 60 % increase in the ability to optimally solve C TÆMS problems in a reasonable amount of time and in a distributed manner as a result of applying our mapping and domain pruning algorithms. 1
Human Face Verification by Robust 3D Surface Alignment
, 2006
"... Traditional 2D face recognition systems are not tolerant to changes in pose, lighting and expression. This dissertation explores the use of 3D data to improve face recognition by accounting for these variations. A two step, fully automatic, 3D surface alignment algorithm is developed to correlate th ..."
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Cited by 6 (1 self)
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Traditional 2D face recognition systems are not tolerant to changes in pose, lighting and expression. This dissertation explores the use of 3D data to improve face recognition by accounting for these variations. A two step, fully automatic, 3D surface alignment algorithm is developed to correlate the surfaces of two 3D face scans. In the first step, key anchor points such as the tip of the nose are used to coarsely align two face scans. In the second step, the Iterative Closest Point (ICP) algorithm is used to finely align the scans. The quality of the face alignment is studied in depth using a Surface Alignment Measure (SAM). The SAM is the root mean squared error over all the control points used in the ICP algorithm, after trimming to account for noise in the data. This alignment algorithm is fast (<2 seconds on a 3.2GHz P4) and robust to noise in the data (<10 % spike noise). Extensive experiments were conducted to show that the alignment algorithm can tolerate up to 15 ◦ of variation in pose due to roll and pitch, and 30 ◦ of variation in yaw. It is shown that this level of pose tolerance easily covers the normal pose variation of a database of over 275 cooperative
Constraint propagation for domain bounding in distributed task scheduling
 Proceedings of Principles and Practice of Constraint Programming, Lecture Notes in Computer Science
, 2006
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Minimal Perturbation Problem – A Formal View. Neural Network World 13(5
, 2003
"... Abstract. Formulation of many reallife problems evolves as the problem is being solved. These changes are typically initiated by a user intervention or by changes in the environment. In this paper, we propose a formal description of so called minimal perturbation problem that allows an “automated” ..."
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Cited by 2 (2 self)
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Abstract. Formulation of many reallife problems evolves as the problem is being solved. These changes are typically initiated by a user intervention or by changes in the environment. In this paper, we propose a formal description of so called minimal perturbation problem that allows an “automated” modification of the (partial) solution when the problem formulation changes. Our model is defined for constraint satisfaction problems with emphasis put on finding a solution anytime even for overconstrained problems.
2C3: From ArcConsistency to 2Consistency
"... Arc consistency algorithms are widely used to prune the search space of Constraint Satisfaction Problems (CSPs). Since many researchers associate arc consistency with binary normalized CSPs, there is a confusion between the notion of arc consistency and 2consistency. 2consistency guarantees that a ..."
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Cited by 1 (1 self)
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Arc consistency algorithms are widely used to prune the search space of Constraint Satisfaction Problems (CSPs). Since many researchers associate arc consistency with binary normalized CSPs, there is a confusion between the notion of arc consistency and 2consistency. 2consistency guarantees that any instantiation of a value to a variable can be consistently extended to any second variable. Thus, 2consistency can be stronger than arcconsistency in binary CSPs. In this paper, we present a new algorithm, called 2C3, which achieves 2consistency in binary and nonnormalized CSPs. This algorithm is a reformulation of the wellknown AC3 algorithm. The evaluation section shows that 2C3 is able to prune more search space than AC3 and AC4.
A finegrained arcconsistency algorithm for nonnormalized constraint satisfaction problems
 International Journal of Applied Mathematics and Computer Science 21(4): 733–744, DOI
, 2011
"... Constraint programming is a powerful software technology for solving numerous reallife problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NPcomplete so filtering techniques to redu ..."
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Constraint programming is a powerful software technology for solving numerous reallife problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NPcomplete so filtering techniques to reduce the search space are still necessary. Arcconsistency algorithms are widely used to prune the search space. The concept of arcconsistency is bidirectional, i.e., it must be ensured in both directions of the constraint (direct and inverse constraints). Two of the most wellknown and frequently used arcconsistency algorithms for filtering CSPs are AC3 and AC4. These algorithms repeatedly carry out revisions and require support checks for identifying and deleting all unsupported values from the domains. Nevertheless, many revisions are ineffective, i.e., they cannot delete any value and consume a lot of checks and time. In this paper, we present AC4OP, an optimized version of AC4 that manages the binary and nonnormalized constraints in only one direction, storing the inverse founded supports for their later evaluation. Thus, it reduces the propagation phase avoiding unnecessary or ineffective checking. The use of AC4OP reduces the number of constraint checks by 50 % while pruning the same search space as AC4. The evaluation section shows the improvement of AC4OP over AC4, AC6 and AC7 in random and nonnormalized instances.
Propagation by selective initialization and its application to numerical constraint satisfaction problems
 Department of Computer Science, University of Victoria
, 2004
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From Type Inference to Configuration
 IN THE ESSENCE OF COMPUTATION: COMPLEXITY, ANALYSIS, TRANSFORMATION. ESSAYS DEDICATED 12
, 2002
"... A product line is a set of products and features with constraints on which subsets are available. Numerous configurators have been made available by product line vendors on the internet, in which procurers can experiment with the different options, e.g. how the selection of one product or feature en ..."
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A product line is a set of products and features with constraints on which subsets are available. Numerous configurators have been made available by product line vendors on the internet, in which procurers can experiment with the different options, e.g. how the selection of one product or feature entails or precludes the selection of another product or feature. We explore an approach to configuration inspired by type inference technology. The main contributions of the paper are a formalization of the configuration problemtha t includes aspects related to the interactive dialogue between the user and the system, a result stating that the configuration problem thus formalized has at least exponential complexity, and some techniques for computing approximate solutions more efficiently. While a substantial number of papers precede the present one in formalizing configuration as a constraint satisfaction problem, few address the aspects concerning interactivity between the user and the system.
Constraint Logic Programming Applied to the Resolution of a Problem of picking of Warehouse SIGMUNDO PREISSLER JUNIOR 1
, 2007
"... Abstract. In this paper we apply logical programming with constraints to the problem of minimizing operational costs of a mobile agent that searches and moves objects in shelves, obeying a known physical configuration. ..."
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Abstract. In this paper we apply logical programming with constraints to the problem of minimizing operational costs of a mobile agent that searches and moves objects in shelves, obeying a known physical configuration.
Preface
, 2010
"... The areas of AI planning and scheduling have seen important advances thanks to application of constraint satisfaction and optimisation techniques. Efficient constraint handling is important for realworld problems in planning, scheduling, and resource allocation to competing goal activities over tim ..."
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The areas of AI planning and scheduling have seen important advances thanks to application of constraint satisfaction and optimisation techniques. Efficient constraint handling is important for realworld problems in planning, scheduling, and resource allocation to competing goal activities over time in the presence of complex statedependent constraints. Approaches to these problems must integrate resource allocation and plan synthesis capabilities. We need to manage complex problems where planning, scheduling, and constraint satisfaction must be interrelated, which entail a great potential of application. This workshop, the fifth in a series, aims at providing a forum for meeting and exchanging ideas and novel works in the field of AI planning, scheduling, and constraint satisfaction techniques, and the many relationships that exist among them. In fact, most of the accepted papers are based on combined approaches of constraint satisfaction for planning, scheduling, and mixing planning