International audienceAn important feature in designing algorithms to solve Constraint Satisfaction Problems (CSP) is the definition of a branching heuristic to explore efficiently the search space and exploit the problem structure. We propose Conflict-History Search (CHS), a new dynamic and adaptive branching heuristic for CSP solving. It is based on the search history by considering the temporality of search failures. To achieve that, we use the exponential recency weighted average to estimate the evolution of the hardness of constraints throughout the search. The experimental evaluation on XCSP3 instances shows that integrating CHS to solvers based on MAC obtains competitive results and can improve those obtained through other heuristics...
AbstractA constraint satisfaction problem (CSP) is said to be overconstrained if it does not have a ...
Building adaptive constraint solvers is a major challenge in constraint programming. An important li...
Abstract Designing a search heuristic for constraint programming that is reliable across problem dom...
International audienceAn important feature in designing algorithms to solve Constraint Satisfaction ...
International audienceBranching heuristic is an important module in algorithms dedicated to solve Co...
International audienceThe variable ordering heuristic is an important module in algorithms dedicated...
International audienceReinforcement learning has shown its relevance in designing search heuristics ...
International audienceIt is well-known that variable ordering heuristics play a central role in solv...
In this paper, we introduce a new solving algorithm for Constraint Satisfaction Problems (CSP). It p...
In this paper, we are interested in enumerative resolution methods for combinatorial optimiza-tion (...
In this paper, we are interested in enumerative resolution methods for combinatorial optimiza-tion (...
Abstract—Constraint satisfaction problems (CSP) are defined by a set of variables, where each variab...
AbstractSearch algorithms for solving csp (Constraint Satisfaction Problems) usually fall into one o...
The most advanced implementation of adaptive constraint processing with Constraint Handling Rules (C...
International audienceIn this paper, we are interested in enumerative resolution methods for combina...
AbstractA constraint satisfaction problem (CSP) is said to be overconstrained if it does not have a ...
Building adaptive constraint solvers is a major challenge in constraint programming. An important li...
Abstract Designing a search heuristic for constraint programming that is reliable across problem dom...
International audienceAn important feature in designing algorithms to solve Constraint Satisfaction ...
International audienceBranching heuristic is an important module in algorithms dedicated to solve Co...
International audienceThe variable ordering heuristic is an important module in algorithms dedicated...
International audienceReinforcement learning has shown its relevance in designing search heuristics ...
International audienceIt is well-known that variable ordering heuristics play a central role in solv...
In this paper, we introduce a new solving algorithm for Constraint Satisfaction Problems (CSP). It p...
In this paper, we are interested in enumerative resolution methods for combinatorial optimiza-tion (...
In this paper, we are interested in enumerative resolution methods for combinatorial optimiza-tion (...
Abstract—Constraint satisfaction problems (CSP) are defined by a set of variables, where each variab...
AbstractSearch algorithms for solving csp (Constraint Satisfaction Problems) usually fall into one o...
The most advanced implementation of adaptive constraint processing with Constraint Handling Rules (C...
International audienceIn this paper, we are interested in enumerative resolution methods for combina...
AbstractA constraint satisfaction problem (CSP) is said to be overconstrained if it does not have a ...
Building adaptive constraint solvers is a major challenge in constraint programming. An important li...
Abstract Designing a search heuristic for constraint programming that is reliable across problem dom...