LIP6 1999/015

• Thesis
  S.A.G.A.C.E.
  Solution Algorithmique Génétique pour lAnticipation de Comportements Evolutifs Application aux jeux à information complète et imparfaite
• Ch. Meyer
• 268 pages - 06/29/1999- document en - http://www.lip6.fr/lip6/reports/1999/lip6.1999.015.ps.gz - 3,128 Ko
• Contact : Christophe.Meyer (at) nulllip6.fr
• Ancien Thème : APA
In a world where men increasingly interact with hardware and/or software, it is advisable to give machines the means to adapt to their users. The machine should serve Man and not the reverse. In order to maximize efficiency, it has to be autonomous and capable of anticipating the users needs, desires and behaviors. The task is complicated by the fact that Man is not a machine himself : he is adaptive, changes his mind, often acts irrationally
The work that is described in this thesis lies within this framework; It concerns the development of a modular method for anticipating changing (adaptive) behaviors : S.A.G.A.C.E.
Games allow machines to confront humans in a context where they must make the most of their abilities of analysis, reflection and adaptation. The implementation of a system capable of anticipating human strategies must allow, in the long run, to manage the anticipation of human behavior in many other activities and thus to fulfil, at least partially, the above mentioned objective.
• Keywords : Anticipation, Learning, Games, Human player modelling, Game theory
• Publisher : Valerie.Mangin (at) nulllip6.fr