Interactive tasks such as online configuration can be modeled as constraint satisfaction problems. These can be solved interactively by a user assigning values to variables. Explanations for failure in constraint programming tend to focus on conflict. However, what is often desirable is an explanation that is corrective in the sense that it provides the basis for moving forward in the problem-solving process. This paper defines this notion of corrective explanation and demonstrates that a greedy search approach performs very well on a large real-world configuration problem
Constraint programming is a research topic benefiting from many other areas: discrete mathematics, n...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...
Complete algorithms for constraint solving typically exploit properties like (in)consistency or inte...
In this work we explore the problem of generating explanations for configuration problems using the ...
International audienceConstraint satisfaction problems or CSP are very often used to formalize produ...
AbstractMost of the algorithms developed within the Constraint Satisfaction Problem (CSP) framework ...
International audienceMost of the algorithms developed within the Constraint Satisfaction Problem (C...
Research effort in constraint satisfaction has traditionally been devoted to curbing the exponential...
. Constraint satisfaction problems have wide application in artificial intelligence. They involve fi...
bb modif 28/02/02International audienceMost of the algorithms developed within the Constraint Satisf...
Abstract. Recent work have exhibited specific structure among combinatorial problem instances that c...
: This paper describes a framework for expressing and solving combinatorial problems. The framework ...
In the constraint satisfaction problem (CSP) formulation used in artificial intelligence, the variab...
The Constraint Satisfaction Problem (CSP) is ubiquitous in artificial intelligence. It has a wide ap...
Many combinatorial problems can be represented naturally as constraint satisfaction problems (CSP). ...
Constraint programming is a research topic benefiting from many other areas: discrete mathematics, n...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...
Complete algorithms for constraint solving typically exploit properties like (in)consistency or inte...
In this work we explore the problem of generating explanations for configuration problems using the ...
International audienceConstraint satisfaction problems or CSP are very often used to formalize produ...
AbstractMost of the algorithms developed within the Constraint Satisfaction Problem (CSP) framework ...
International audienceMost of the algorithms developed within the Constraint Satisfaction Problem (C...
Research effort in constraint satisfaction has traditionally been devoted to curbing the exponential...
. Constraint satisfaction problems have wide application in artificial intelligence. They involve fi...
bb modif 28/02/02International audienceMost of the algorithms developed within the Constraint Satisf...
Abstract. Recent work have exhibited specific structure among combinatorial problem instances that c...
: This paper describes a framework for expressing and solving combinatorial problems. The framework ...
In the constraint satisfaction problem (CSP) formulation used in artificial intelligence, the variab...
The Constraint Satisfaction Problem (CSP) is ubiquitous in artificial intelligence. It has a wide ap...
Many combinatorial problems can be represented naturally as constraint satisfaction problems (CSP). ...
Constraint programming is a research topic benefiting from many other areas: discrete mathematics, n...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...
Complete algorithms for constraint solving typically exploit properties like (in)consistency or inte...