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EDBT 2026 Demo / reviewers in the wild / expert

A. Farhi

dblp:20/5366 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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
Multi-agent systems · 100%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems
dynamic scheduling		 0.011999
A Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS) · ICRA 1999
Knowledge, reasoning and agents › Multi-agent systems › distributed scheduling
multi-agent scheduling		 0.011999
A Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS) · ICRA 1999
Knowledge, reasoning and agents › Multi-agent systems
flexible manufacturing systems		 0.011999
A Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS) · ICRA 1999

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

contract net protocol · 0.0
YearPublicationVenuePosition
1999 A Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS)
abstract
Deals with a multi-agent architecture and a negotiation protocol for the dynamic scheduling of flexible manufacturing systems. The originality of the multi-agent architecture resides in the existence of task agents and resource agents. The multi-contract net protocol proposed, is an innovation with regard to the contract-net protocol due to the way that it makes it possible to negotiate several tasks concurrently, in real time and with more optimal results taking into account uncertainty and conflict situations in the scheduling of operations. The paper, also, stresses the efficiency and the optimality of the distributed implementation.
Djamila Ouelhadj, Chihab Hanachi, Adlene Moualek, A. Farhi
 ICRA4