@incollection{fdi:010055252,
  title = {{K}nowledge revision in systems based on an informed tree search strategy : application to cartographic generalisation},
  author = {{T}aillandier, {P}. and {D}uch{\^e}ne, {C}. and {D}rogoul, {A}lexis},
  editor = {},
  language = {{ENG}},
  abstract = {{M}any real world problems can be expressed as optimisation problems. {S}olving this kind of problems means to find, among all possible solutions, the one that maximises an evaluation function. {O}ne approach to solve this kind of problem is to use an informed search strategy. {T}he principle of this kind of strategy is to use problem-specific knowledge beyond the definition of the problem itself to find solutions more efficiently than with an uninformed strategy. {T}his kind of strategy demands to define problem-specific knowledge (heuristics). {T}he efficiency and the effectiveness of systems based on it directly depend on the used knowledge quality. {U}nfortunately, acquiring and maintaining such knowledge can be fastidious. {T}he objective of the work presented in this paper is to propose an automatic knowledge revision approach for systems based on an informed tree search strategy. {O}ur approach consists in analysing the system execution logs and revising knowledge based on these logs by modelling the revision problem as a knowledge space exploration problem. {W}e present an experiment we carried out in an application domain where informed search strategies are often used: cartographic generalisation},
  keywords = {{INTELLIGENCE} {ARTIFICIELLE} ; {ALGORITHME} ; {OPTIMISATION} {MATHEMATIQUE} ; {HEURISTIQUE}},
  booktitle = {{T}he fifth international conference on soft computing as transdisciplinary science and technology : proceedings},
  numero = {},
  pages = {273--278},
  address = {{D}anvers},
  publisher = {{ACM}},
  series = {},
  year = {2008},
  DOI = {10.1145/1456223.1456281},
  ISBN = {978-1-60558-046-3},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055252},
}