Path: utzoo!attcan!uunet!samsung!dali.cs.montana.edu!milton!jsp From: jsp@milton.u.washington.edu (Jeff Prothero) Newsgroups: comp.ai.philosophy Subject: Re: emergence Message-ID: Date: 3 Oct 90 19:30:40 GMT References: <3531@media-lab.MEDIA.MIT.EDU> Sender: news@milton.u.washington.edu Organization: Biological Structure, U of Wash, Seattle Lines: 26 In-reply-to: mt@media-lab.MEDIA.MIT.EDU's message of 3 Oct 90 00:40:52 GMT Perhaps the key characteristic of an 'emergent phenomenon' is that it has interesting characteristics which it possesses *independently* of the underlying (implementation) system? We avoid analysing computer programs in terms of electron diffusion not just because such an analysis would be awkward, opaque and difficult, but because it is, in a fundamental sense, *irrelevant*. The same computer program could be run on a VLSI-based machine, a vacuum-tube based machine, an optical-based machine, a Tinker-Toy(R)-based machine, or hand-interpreted by a human. Barring implementation defects, the behavior of the program will be the same in every case. Understanding a computer program which implements Euclid's GCD just does not depend in any interesting fashion on the physics of TinkerToys, even if the program is destined to be run on a computer constructed from TinkerToys. Perhaps "emergent systems" generally may be characterised by a similar resilient self-integrity: They possess interesting properties which are independent of the underlying system, and which in fact may be based on quite different underlying systems. Intelligent systems may possess properties which are quite independent of the specific characteristics of neurons, and may (potentially?) be manifested on systems with radically different low-level architectures. Studying neurons may tell us as much about intelligence as studying TinkerToys does about Euclid's GCD algorithm.