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Sébastien Gamblin

dblp:246/2981 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0005-6508-0958ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1

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
Knowledge representation and reasoning · 87% Multi-agent systems · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
epistemic reasoning
0.412019
Hintikka's World: Scalable Higher-order Knowledge · IJCAI 2019
Knowledge, reasoning and agents › Knowledge representation and reasoning › logic in computer science › logical foundations › non-classical logics › epistemic logic
higher-order knowledge
0.412019
Hintikka's World: Scalable Higher-order Knowledge · IJCAI 2019
YearPublicationVenuePosition
2025 Symbolic Representation for Graded Dynamic Epistemic Logic
Sébastien Gamblin
PRIMA1
2019 Hintikka's World: Scalable Higher-order Knowledge
abstract
Hintikka's World is a graphical and pedagogical tool that shows how artificial agents can reason about higher-order knowledge. In this demonstration paper, we present the implementation of symbolic models in Hintikka's World. They enable the tool to scale, by helping it to face the state explosion, which makes it possible to provide examples featuring real card games, such as Hanabi.
Tristan Charrier, Sébastien Gamblin, Alexandre Niveau, François Schwarzentruber
IJCAI2