Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Path: utzoo!mnetor!seismo!husc6!mit-eddie!ll-xn!ames!lll-tis!ptsfa!ihnp4!homxb!houxm!houdi!marty1 From: marty1@houdi.UUCP (M.BRILLIANT) Newsgroups: comp.ai,comp.cog-eng Subject: Re: The symbol grounding problem (Reply to Ken Laws on ailist) Message-ID: <1166@houdi.UUCP> Date: Tue, 16-Jun-87 13:41:50 EDT Article-I.D.: houdi.1166 Posted: Tue Jun 16 13:41:50 1987 Date-Received: Sun, 21-Jun-87 08:37:34 EDT References: <764@mind.UUCP> <768@mind.UUCP> <770@mind.UUCP> <6174@diamond.BBN.COM> <849@mind.UUCP> Organization: AT&T Bell Laboratories, Holmdel Lines: 52 Summary: Keeping our own symbols grounded; decoding continuous signals Xref: mnetor comp.ai:552 comp.cog-eng:135 In article <849@mind.UUCP>, harnad@mind.UUCP (Stevan Harnad) writes: > .... Invertibility could fail to capture the standard A/D distinction, > but may be important in the special case of mind-modeling. Or it could > turn out not to be useful at all.... So what do you think is essential: (A) literally analog transformation, (B) invertibility, or (C) preservation of significant relational functions? > ..... what I've said about the grounding problem and the role > of nonsymbolic representations (analog and categorical) would stand > independently of my particular criterion for analog; substituting a more > standard one leaves just about all of the argument intact..... Where does that argument stand now? Can we restate it in terms whose definitions we all agree on? > ..... to get the requisite causality I'm looking > for, the information must be interpretation-independent. Physical > invertibility seems to give you that...... I think invertibility is too strong. It is sufficient, but not necessary, for human-style information-processing. Real people forget awesome amounts of detail, we misunderstand each other (our symbol groundings are not fully invertible), and we thereby achieve levels of communication that often, but not always, satisify us. Do you still say we only need transformations that are analog (invertible) with respect to those features for which they are analog (invertible)? That amounts to limited invertibility, and the next essential step would be to identify the features that need invertibility, as distinct from those that can be thrown away. > Ken Laws on ailist@Stripe.SRI.Com writes: > > ... I am sure that methods for decoding both discrete and > > continuous information in continuous signals are well studied. > > I would be interested to hear from those who are familiar with such work. > It may be that some of it is relevant to cognitive and neural modeling > and even the symbol grounding problems under discussion here. I'm not up to date on these methods. But if you want to get responses from experts, it might be well to be more specific. For monaural sound, decoding can be done with Fourier methods that are in principle continuous. For monocular vision, Fourier methods are used for image enhancement to aid in human decoding, but I think machine decoding depends on making the spatial dimensions discontinous and comparing the content of adjacent cells. M. B. Brilliant Marty AT&T-BL HO 3D-520 (201)-949-1858 Holmdel, NJ 07733 ihnp4!houdi!marty1