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Sébastien Lê Cong

dblp:222/7887 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 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.

Theoretical computer science
1 paper
Computational complexity · 77% Logic in computer science · 23%
Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 100%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
epistemic planning
0.312018
Small Undecidable Problems in Epistemic Planning · IJCAI 2018
Computational complexity
undecidability
0.312018
Small Undecidable Problems in Epistemic Planning · IJCAI 2018
Logic in computer science › epistemic logic
dynamic epistemic logic
0.112018
Small Undecidable Problems in Epistemic Planning · IJCAI 2018
YearPublicationVenuePosition
2018 Small Undecidable Problems in Epistemic Planning
abstract
Epistemic planning extends classical planning with knowledge and is based on dynamic epistemic logic (DEL). The epistemic planning problem is undecidable in general. We exhibit a small undecidable subclass of epistemic planning over 2-agent S5 models with a fixed repertoire of one action, 6 propositions and a fixed goal. We furthermore consider a variant of the epistemic planning problem where the initial knowledge state is an automatic structure, hence possibly infinite. In that case, we show the epistemic planning problem with 1 public action and 2 propositions to be undecidable, while it is known to be decidable with public actions over finite models. Our results are obtained by reducing the reachability problem over small universal cellular automata. While our reductions yield a goal formula that displays the common knowledge operator, we show, for each of our considered epistemic problems, a reduction into an epistemic planning problem for a common-knowledge-operator-free goal formula by using 2 additional actions.
Sébastien Lê Cong, Sophie Pinchinat, François Schwarzentruber
IJCAI1