The aim of this paper is to introduce a general framework for preference-based search in state space graphs with a focus on the search of the preferred solutions. After introducing a formal definition of preference-based search problems, we introduce the PBA ∗ algorithm, a generalization of the A ∗ algorithm, designed to process quasi-transitive preference relations defined over the set of solutions. Then, considering a particular subclass of preference structures characterized by two axioms called Weak Preadditivity and Monotonicity, we establish termination, completeness and admissibility results for PBA ∗. We also show that previous generalizations of A ∗ are particular instances of PBA ∗. The interest of our algorithm is illustrated on ...
Existing preference prediction techniques can require that an entire preference structure be constru...
A simple logic of conditional preferences is defined, with a language that allows the compact repres...
Preference logics and AI preference representation languages are both concerned with reasoning about...
International audienceComparison of solutions in combinatorial problems is often based on an additiv...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
Preference-based search (PBS) is a new search procedure for solving combinatorial optimization probl...
The aim of this paper is to propose a new approach interweaving preference elicitation and search to...
This paper is devoted to the determination of well-balanced solutions in search problems involving m...
The aim of this paper is to introduce and solve new search problems in multiobjective state space gr...
This paper is devoted to the determination of well-balanced solutions in search problems involving m...
This paper is devoted to the the search of robust solutions in state space graphs when costs depend ...
Matching under preferences involves matching agents to one another, subject to various optimality cr...
Many real-world AI problems (e.g. in configuration) are weakly constrained, thus requiring a mechani...
Existing preference prediction techniques can require that an entire preference structure be constru...
A simple logic of conditional preferences is defined, with a language that allows the compact repres...
Preference logics and AI preference representation languages are both concerned with reasoning about...
International audienceComparison of solutions in combinatorial problems is often based on an additiv...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
In multiobjective state space graph problems, each solution-path is evaluated by a cost vector. Thes...
Preference-based search (PBS) is a new search procedure for solving combinatorial optimization probl...
The aim of this paper is to propose a new approach interweaving preference elicitation and search to...
This paper is devoted to the determination of well-balanced solutions in search problems involving m...
The aim of this paper is to introduce and solve new search problems in multiobjective state space gr...
This paper is devoted to the determination of well-balanced solutions in search problems involving m...
This paper is devoted to the the search of robust solutions in state space graphs when costs depend ...
Matching under preferences involves matching agents to one another, subject to various optimality cr...
Many real-world AI problems (e.g. in configuration) are weakly constrained, thus requiring a mechani...
Existing preference prediction techniques can require that an entire preference structure be constru...
A simple logic of conditional preferences is defined, with a language that allows the compact repres...
Preference logics and AI preference representation languages are both concerned with reasoning about...