Xref: utzoo sci.math.stat:1825 comp.ai:8173 Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!usc!zaphod.mps.ohio-state.edu!sol.ctr.columbia.edu!emory!gatech!bloom-beacon!eru!hagbard!sunic!mcsun!corton!imag!bessiere From: bessiere@imag.imag.fr (Pierre Bessiere) Newsgroups: sci.math.stat,comp.ai Subject: Paper available via ftp Message-ID: <16262@imag.imag.fr> Date: 6 Dec 90 13:32:36 GMT Reply-To: bessiere@imag.fr (Pierre Bessiere) Followup-To: sci.math.stat Organization: IMAG Institute, University of Grenoble, France Lines: 78 Hello evrybody, A copy of a paper appeared in conference COGNITIVA90 held in Madrid in november 1990, is now avalaible by ftp. ---------------------------- Title: TOWARD A SYNTHETIC COGNITIVE PARADIGM: PROBABILISTIC INFERENCE Abstract: Cognitive science is a very active field of scientific interest. It turns out to be a "melting pot" of ideas coming from very different areas. One of the principal hopes is that some synthetic cognitive paradigms will emerge from this interdisciplinary "brain storming". The goal of this paper is to answer the question: " Given the state of the art, is there any hints indicating the emergence of such synthetic paradigms?" The main thesis of the paper is that there is a good candidate, namely, the PROBABILISTIC INFERENCE paradigm. In support of the above thesis the structure of the paper is as follows: - in a first part, we identify five criteria to qualify as a synthetic cognitive paradigm (validity, self-consistency, competence, feasability and mimetic power); - in the second section, the principles of probabilistic inference are reviewed and justifications of validity and self-consistency of this paradigm are given (Marr's computational level); - then, the competence criterion is dicussed, considering the efficiency of probabilistic inference for dealing with the different cognitive riddles and analyzing the relationships of probabilistic inference with several of the usual connexionist formalisms (Marr's algorithmic level); - the criteria of feasibility (condition of computer implementation) and mimetic power (adequation with what is known of the architecture of the nervous system) are finally considered in the fourth part (Marr's implementation level). As a conclusion, it will appear that probabilistic inference is at least a very intersting framework to get a synthetic overview of a number of works in the area and to identify and formalize the most puzzling questions. Some of these questions will be listed. In fact, probabilistic inference will appear finally to be able to play the same role for computational cognitive science that formal logic has played for classical symbolic Artificial Intelligence: a sound mathematical foundation serving as a guide line, as a constant reference and as a source of inspiration. -------------------------- The following procedure should give you a copy of the paper: ftp 129.88.32.1 Name ( ... ): anonymous Password: anything ftp> cd pub/SYMPA ftp> dir ftp> bin ftp> get Proba-Inf.ps.Z ftp> quit (!) uncompress < Proba-Inf.ps.Z | lpr -l -Pprinter Please send any questions or comments to: Pierre BESSIERE *************** IMAG/LGI phone: BP 53X Work: 33/76.51.45.72 38041 Grenoble Cedex Home: 33/76.51.16.15 FRANCE Fax: 33/76.44.66.75 Telex:UJF 980 134 F E-Mail: bessiere@imag.imag.fr C'est au savant moderne que convient, plus qu'a tout autre, l'austere conseil de Kipling: "Si tu peux voir s'ecrouler soudain l'ouvrage de ta vie, et te remettre au travail, si tu peux souffrir, lutter, mourrir sans murmurer, tu seras un homme , mon fils." Dans l'oeuvre de la science seulement on peut aimer ce qu on detruit, on peut continuer le passe en le niant, on peut venerer son maitre en le contredisant. GASTON BACHELARD Brought to you by Super Global Mega Corp .com