Interactive Learning of Expert Criteria for Rescue Simulations

  • Thanh-Quang Chu
  • Alain Boucher
  • Alexis Drogoul
  • Duc-An Vo
  • Hong-Phuong Nguyen
  • Jean-Daniel Zucker
Conference paper

DOI: 10.1007/978-3-540-89674-6_16

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5357)
Cite this paper as:
Chu TQ., Boucher A., Drogoul A., Vo DA., Nguyen HP., Zucker JD. (2008) Interactive Learning of Expert Criteria for Rescue Simulations. In: Bui T.D., Ho T.V., Ha Q.T. (eds) Intelligent Agents and Multi-Agent Systems. PRIMA 2008. Lecture Notes in Computer Science, vol 5357. Springer, Berlin, Heidelberg

Abstract

The goal of our work is to build a DSS (Decision Support System) to support resource allocation and planning for natural disaster emergencies in urban areas such as Hanoi in Vietnam. The first step has been to conceive a multi-agent environment that supports simulation of disasters, taking into account geospatial, temporal and rescue organizational information. The problem we address is the acquisition of situated expert knowledge that is used to organize rescue missions. We propose an approach based on participatory techniques, interactive learning and machine learning. This paper presents an algorithm that incrementally builds a model of the expert knowledge by online analysis of its interaction with the simulator’s proposed scenario.

Keywords

Rescue Management Multi-agent Simulation Decision Support Systems Knowledge Extraction Participatory Learning Interactive Learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Thanh-Quang Chu
    • 1
    • 2
  • Alain Boucher
    • 2
  • Alexis Drogoul
    • 1
    • 2
  • Duc-An Vo
    • 1
    • 2
  • Hong-Phuong Nguyen
    • 3
  • Jean-Daniel Zucker
    • 1
  1. 1.IRD, UR079-GEODESBondy CedexFrance
  2. 2.AUF-IFI, MSIHa NoiViet Nam
  3. 3.IG-VASTHanoiVietnam

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