Interactive Learning of Expert Criteria for Rescue Simulations View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2008

AUTHORS

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

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. More... »

PAGES

127-138

Book

TITLE

Intelligent Agents and Multi-Agent Systems

ISBN

978-3-540-89673-9
978-3-540-89674-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-89674-6_16

DOI

http://dx.doi.org/10.1007/978-3-540-89674-6_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051671094


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