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From: DOCTORJ@SLACVM.SLAC.STANFORD.EDU (Jon J Thaler)
Newsgroups: comp.ai.philosophy
Subject: Re: Continuous vs discrete
Message-ID: <91102.201225DOCTORJ@SLACVM.SLAC.STANFORD.EDU>
Date: 13 Apr 91 04:12:24 GMT
Organization: Stanford Linear Accelerator Center
Lines: 11

There are two distinct aspects of the "Continuous vs Discrete" issue, and
it seems to me that the discussion has focussed only on one.  They are
* Discreteness due to the finite number of bits in computer representations
  of numbers.  This has been the main topic of conversation, and I agree with
  those who say that it's not an issue.
* Discreteness (or granularity) of the lattice on which the simulation is
  being run.  This is the aspect that worries me, since it is a serious problem
  in the modeling of other physical systems (eg, weather).  Do any people
  know of "proofs" (in the mathematical sense) or at least empirical evidence
  that the highly granular approach to AI models is a realistic approach to
  the (nearly) continuous system (the brain) that is being studied?