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- Thomas Schiex, Hélène Fargier, Gérard Verfaillie
- IJCAI
- 1995

In order to deal with over-constrained Constraint Satisfaction Problems, various extensions of the CSP framework have been considered by taking into account costs, uncertainties, preferences, priorities...Each extension uses a specific mathematical operator (+;max : : :) to aggregate constraint violations. In this paper, we consider a simple algebraic… (More)

- Stefano Bistarelli, Ugo Montanari, Francesca Rossi, Thomas Schiex, Gérard Verfaillie, Hélène Fargier
- Constraints
- 1999

In this paper we describe and compare two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. While comparing the two approaches, we show how to pass from one to the other one,… (More)

- Thomas Schiex, Gérard Verfaillie
- ICTAI
- 1993

Many AI synthesis problems such as planning, scheduling or design may be encoded in a constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all given constraints between these variables. However, for many real tasks, the set of constraints to consider may… (More)

- Gérard Verfaillie, Thomas Schiex
- AAAI
- 1994

Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environment, the user or other agents in the framework of a distributed system. In this context, computing a new solution from scratch after each problem change is possible, but has two… (More)

- Gérard Verfaillie, Michel Lemaître
- CP
- 2001

- Stefano Bistarelli, Hélène Fargier, Ugo Montanari, Francesca Rossi, Thomas Schiex, Gérard Verfaillie
- Over-Constrained Systems
- 1995

We introduce two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction , and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. We then compare the two approaches and we discuss the relationship between them.

- Gérard Verfaillie, Narendra Jussien
- Constraints
- 2005

This article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 (Ninth International Conference on Principles and Practice of Constraint Programming) in Kinsale, Ireland (Verfaillie, G., & Jussien, N. (2003). It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of… (More)

- Pierre Dago, Gérard Verfaillie
- ICTAI
- 1996

In the frame of classical Constraint Satisfaction Problems (CSPs), the backtrack tree search, combined with learning methods, presents a double advantage : for static solving, it improves the search speed by avoiding redundant explorations; for dynamic solving (after a slight change of the problem), it reuses the previous searches to build a new solution… (More)

- Gérard Verfaillie, Michel Lemaître, Thomas Schiex
- AAAI/IAAI, Vol. 1
- 1996

If the Constraint Satisfaction framework has been extended to deal with Constraint Optimization problems, it appears that optimization is far more complex than satisfaction. One of the causes of the inefficiency of complete tree search methods, like Depth First Branch and Bound, lies in the poor quality of the lower bound on the global valuation of a… (More)

- E. Bensana, Michel Lemaître, Gérard Verfaillie
- Constraints
- 1999

The daily management of an earth observation satellite is a challenging combinatorial optimization problem. This problem can be roughly stated as follows: given (1) a set of candidate images for the next day, each one associated with a weight reflecting its importance, (2) a set of imperative constraints expressing physical limitations (no overlapping… (More)