Multi-Agents Systems for Cartographic Generalization: Feedback from Past and On-going Research - Archive ouverte HAL Access content directly
Reports (Research Report) Year : 2018

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

Abstract

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.

Keywords

Fichier principal
Vignette du fichier
ducheneEtAl_agent_report (1).pdf (1.72 Mo) Télécharger le fichier
Loading...

Dates and versions

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

Identifiers

  • HAL Id : hal-01682131 , version 1

Cite

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⟩
278 View
243 Download

Share

Gmail Facebook X LinkedIn More