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Inger Klein

dblp:47/70 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1999
0000-0002-9148-0585ORCID · corroborated

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

Artificial intelligence and machine learning · 2Databases, data management, data science and information retrieval · 1 · 1 first-authorGraphics, 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
Planning, search and constraint satisfaction · 100%
Theoretical computer science
1 paper
Computational complexity · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning
parallel planning
0.011991
Parallel Non-Binary Planning in Polynomial Time · IJCAI 1991

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

complexity analysis · 0.0
YearPublicationVenuePosition
1999 Efficient planning for a miniature assembly line
Inger Klein, Peter Jonsson, Christer Bäckström
Artif. Intell. Eng.1
1991 Parallel Non-Binary Planning in Polynomial Time
Christer Bäckström, Inger Klein
IJCAI2
1991 Planning in polynomial time: the SAS-PUBS class
abstract
This article describes a polynomial‐time, O(n3), planning algorithm for a limited class of planning problems. Compared to previous work on complexity of algorithms for knowledge‐based or logic‐based planning, our algorithm achieves computational tractability, but at the expense of only applying to a significantly more limited class of problems. Our algorithm is proven correct, and it always returns a parallel minimal plan if there is a plan at all. Cet article décrit un algorithme de planification de temps polynomial O(n3) pour une classe restreinte de problemes de planification. Contrairement aux travaux précédents sur la complexité des algorithmes pour la planification basée sur la logique ou les connaissances, l' algorithme dont il est question dans cet article permet d' obtenir la tractabilityé computationnelle; cependant, il ne peut ětre appliqué qu'à une catégorie beaucoup plus restreinte de problèmes. Cet algorithme s'est done révélé correct et il génère toujours un plan minimal en parallèle lorsqu'il y en a un.
Christer Bäckström, Inger Klein
Comput. Intell.2