@article{fdi:010049192,
  title = {{I}nteractive learning of independent experts criteria for rescue simulations},
  author = {{C}hu, {T}. {Q}. and {D}rogoul, {A}lexis and {B}oucher, {A}. and {Z}ucker, {J}ean-{D}aniel},
  editor = {},
  language = {{ENG}},
  abstract = {{E}fficient response to natural disasters has an increasingly important role in limiting the toll on human life and property. {T}he work we have undertaken seeks to improve existing models by building a {D}ecision {S}upport {S}ystem ({DSS}) of resource allocation and planning for natural disaster emergencies in urban areas. {A} multi-agent environment is used to simulate disaster response activities, taking into account geospatial, temporal and rescue organizational information. {T}he problem we address is the acquisition of situated expert knowledge that is used to organize rescue missions. {W}e propose an approach based on participatory design and interactive learning which incrementally elicits experts' preferences by online analysis of their interventions with rescue simulations. {A}n additive utility functions are used, assuming mutual preferential independence between decision criteria, as a preference for the elicitation process. {T}he learning algorithm proposed refines the coefficients of the utility function by resolving incremental linear programming. {F}or testing our algorithm, we run rescue scenarios of ambulances saving victims. {T}his experiment makes use of geographical data for the {B}a-{D}inh district of {H}anoi and damage parameters from well-regarded local statistical and geographical resources. {T}he preliminary results show that our approach is initially confident in solving this problem.},
  keywords = {{D}isaster {R}esponse ; {M}ulti-{C}riteria {D}ecision {M}aking ; {D}ecision {S}upport {S}ystem ; {M}ulti-agent {S}imulation ; {I}nteractive {L}earning ; {P}reference {E}licitation ; {U}tility {F}unction ; {P}articipatory {D}esign},
  booktitle = {},
  journal = {{J}ournal of {U}niversal {C}omputer {S}cience},
  volume = {15},
  numero = {13},
  pages = {2701--2725},
  ISSN = {0948-695{X}},
  year = {2009},
  URL = {https://www.documentation.ird.fr/hor/fdi:010049192},
}