Learning/Representation: BBS Call for Commentators

Below is the abstract of a forthcoming target article on: COMPUTATION, REPRESENTATION AND LEARNING by Andy Clark and Chris Thronton This article has been accepted for publication in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal providing Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be current BBS Associates or nominated by a current BBS Associate. To be considered as a commentator for this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send email to: bbs(a)soton.ac.uk or write to: Behavioral and Brain Sciences Department of Psychology University of Southampton Highfield, Southampton SO17 1BJ UNITED KINGDOM http://www.princeton.edu/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS To help us put together a balanced list of commentators, please give some indication of the aspects of the topic on which you would bring your areas of expertise to bear if you were selected as a commentator. An electronic draft of the full text is available for inspection by anonymous ftp (or gopher or world-wide-web) according to the instructions that follow after the abstract. ____________________________________________________________________ TRADING SPACES: COMPUTATION, REPRESENTATION AND THE LIMITS OF UNINFORMED LEARNING Andy Clark Philosophy/Neuroscience/Psychology Program, Washington University in St Louis, Campus Box 1073, St Louis, MO-63130, USA andy(a)twinearth.wustl.edu Chris Thornton, Cognitive and Computing Sciences, University of Sussex, Brighton, BN1 9QH, UK Chris.Thornton(a)cogs.sussex.ac.uk KEYWORDS: Learning, connectionism, statistics, representation, search ABSTRACT: Some regularities enjoy only an attenuated existence in a body of training data. These are regularities whose statistical visibility depends on some systematic re-coding of the data. The space of possible re-codings is, however, infinitely large - it is the space of applicable Turing machines. As a result, mappings which pivot on such attenuated regularities cannot, in general, be found by brute force search. The class of problems which present such mappings we call the class of `type-2 problems'. Type-1 problems, by contrast, present tractable problems of search insofar as the relevant regularities can be found by sampling the input data as originally coded. Type-2 problems, we suggest, present neither rare nor pathological cases. They are rife in biologically realistic settings and in domains ranging from simple animat behaviors to language acquisition. Not only are such problems rife - they are standardly solved! This presents a puzzle. How, given the statistical intractability of these type-2 cases does nature turn the trick? One answer, which we do not pursue, is to suppose that evolution gifts us with exactly the right set of re-coding biases so as to reduce specific type-2 problems to (tractable) type-1 mappings. Such a heavy duty nativism is no doubt sometimes plausible. But we believe there are other, more general mechanisms also at work. Such mechanisms provide general (not task-specific) strategies for managing problems of type-2 complexity. Several such mechanisms are investigated. At the heart of each is a fundamental ploy viz. the maximal exploitation of states of representation already achieved by prior (type-1) learning so as to reduce the amount of subsequent computational search. Such exploitation both characterises and helps make unitary sense of a diverse range of mechanisms. These include simple incremental learning (Elman 1993), modular connectionism (Jacobs, Jordan and Barto 1991), and the developmental hypothesis of `representational redescription' (Karmiloff-Smith A Functional 1979, Karmiloff-Smith PDP 1992). In addition, the most distinctive features of human cognition---language and culture---may themselves be viewed as adaptations enabling this representation/computation trade-off to be pursued on an even grander scale. -------------------------------------------------------------- To help you decide whether you would be an appropriate commentator for this article, an electronic draft is retrievable by anonymous ftp from ftp.princeton.edu according to the instructions below (the filename is bbs.clark). Please do not prepare a commentary on this draft. Just let us know, after having inspected it, what relevant expertise you feel you would bring to bear on what aspect of the article. ------------------------------------------------------------- These files are also on the World Wide Web and the easiest way to retrieve them is with Netscape, Mosaic, gopher, archie, veronica, etc. Here are some of the URLs you can use to get to the BBS Archive: http://www.princeton.edu/~harnad/bbs.html http://cogsci.soton.ac.uk/~harnad/bbs.html gopher://gopher.princeton.edu:70/11/.libraries/.pujournals ftp://ftp.princeton.edu/pub/harnad/BBS/bbs.clark ftp://cogsci.soton.ac.uk/pub/harnad/BBS/bbs.clark To retrieve a file by ftp from an Internet site, type either: ftp ftp.princeton.edu or ftp 128.112.128.1 When you are asked for your login, type: anonymous Enter password as queried (your password is your actual userid: yourlogin(a)yourhost.whatever.whatever - be sure to include the "@") cd /pub/harnad/BBS To show the available files, type: ls Next, retrieve the file you want with (for example): get bbs.clark When you have the file(s) you want, type: quit ---------- Where the above procedure is not available there are two fileservers: ftpmail(a)decwrl.dec.com and bitftp(a)pucc.bitnet that will do the transfer for you. To one or the other of them, send the following one line message: help for instructions (which will be similar to the above, but will be in the form of a series of lines in an email message that ftpmail or bitftp will then execute for you). -------------------------------------------------------------