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Cyril Pain-Barre

dblp:58/5501 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2010
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Speech recognition and synthesis · 50% Planning, search and constraint satisfaction · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Speech recognition and synthesis
search space reduction
0.112007
Filtering, Decomposition and Search Space Reduction for Optimal Sequential Planning · AAAI 2007

Methods — techniques the papers use, named apart from their topics

state-space decomposition · 0.1heuristic search · 0.1
YearPublicationVenuePosition
2010 Minimizing the Number of Actions in Parallel Planning
abstract
In the domain of classical planning one distinguishes plans which are optimal in their number of actions, they are referred as sequential plans, from plans which are optimal in their number of levels, they are referred as parallel plans. Searching optimal sequential plans is generally considered harder than searching optimal parallel plans. Buttner and Rintanen have proposed a search procedure which computes plans whose numbers of levels are fixed and whose numbers of actions are minimal. This procedure is notably used to calculate optimal sequential plans, starting from an optimal parallel plan. In this paper we describe a similar approach, which we have developed from the planner FDP. The idea consists in maintaining two structures, the first one representing the parallel plan and the other representing the sequential plan, performing the choices simultaneously in both structures. The techniques which were developed in FDP to compute sequential plans or parallel plans enable failures detection in the two structures. Experimental results show that this approach is in some cases more efficient than FDP when searching optimal sequential plans.
Stéphane Grandcolas, Cyril Pain-Barre
ICTAI (2)2
2007 Filtering, Decomposition and Search Space Reduction for Optimal Sequential Planning
Stéphane Grandcolas, Cyril Pain-Barre
AAAI2
1998 Using Relevance for Selecting Integrity Constraints which Do Not Interfer in Knowledge Base Update
Cyril Pain-Barre
ECAI1
1996 DEDAL: a DEDuctive and ALgorithmic planning system
Cyril Pain-Barre
ECAI1