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Rapport (Rapport De Recherche) Année : 2018

Multi-Agents Systems for Cartographic Generalization: Feedback from Past and On-going Research

Résumé

Cartographic generalization is a highly local and contextual process where decisions are taken locally to better adjust the transformations used to the local geography. Thus, carto-graphic generalization fits well with the multi-agents paradigm that promotes decentralized and autonomous decision-making. The past years of research in cartographic generalization showed several successful attempts to use multi-agents systems, and this paper provides a feedback on these attempts. We extracted a core modeling of a multi-agents system for generalization and highlighted its main components. Previous propositions of multi-agents generalization processes are described in relation to this core modeling, and feedbacks from experimentations with these processes are discussed to define a research agenda in multi-agents modeling for generalization.

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Dates et versions

hal-01682131 , version 1 (12-01-2018)

Identifiants

  • HAL Id : hal-01682131 , version 1

Citer

Cécile Duchêne, Guillaume Touya, Patrick Taillandier, Julien Gaffuri, Anne Ruas, et al.. Multi-Agents Systems for Cartographic Generalization: Feedback from Past and On-going Research. [Research Report] IGN (Institut National de l’Information Géographique et Forestière); LaSTIG, équipe COGIT. 2018. ⟨hal-01682131⟩
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