Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Path: utzoo!mnetor!uunet!seismo!mcvax!botter!roelw From: roelw@cs.vu.nl (Roel Wieringa) Newsgroups: comp.cog-eng,comp.ai Subject: Re: The symbol grounding problem: Again... grounding? Message-ID: <1523@botter.cs.vu.nl> Date: Thu, 16-Jul-87 05:23:07 EDT Article-I.D.: botter.1523 Posted: Thu Jul 16 05:23:07 1987 Date-Received: Sat, 18-Jul-87 05:57:36 EDT References: <.... <6174@diamond.BBN.COM> <917@mind.UUCP> Reply-To: roelw@cs.vu.nl (Roel Wieringa) Organization: VU Informatica, Amsterdam Lines: 106 Xref: mnetor comp.cog-eng:207 comp.ai:662 In article 512 of comp.ai Peter Berke says that 1. Newell's hypothesis that all human goal-oriented symbolic activity is searching through a problem-space must be taken to mean that human goal-oriented symbolic activity is equivalent to computing, i.e. that it equivalent (mutually simulatable) to a process executed by a Turing machine; 2. but human behavior is not restricted to computing, the process of understanding an ambiguous word (one having 0 meanings, as opposed to an equivocal word, which has more than 1 meanings) being a case in point. Resolving equivocality can be done by searching a problem space; ambiguity cannot be so resolved. If 1 is correct (which requires a proof, as Berke says), then if 2 is correct, we can conclude that not all human behavior is searching through a problem space; the further conclusion then follows that classical AI (using computers and algorithms to reach its goal) cannot reach the goal of implementing human behavior as search through a state space. There are two problems I have with this argument. First, barring a quibble about the choice of the terms "ambiguity" and "equivocality", it seems to me that ambiguity as defined by Berke is really meaninglessness. I assume he does not mean that part of the surplus capacity of humans over machines is that humans can resolve meaninglessness whereas machines cannot, so Berke has not said what he wants to say. Second, the argument applies to classical AI. If one wishes to show that "machines cannot do everything that humans can do," one should find an argument which applies to connection machines, Boltzmann machines, etc. as well. Supposing for the sake of the argument that it is important to show that there is an essential difference between man and machine, I offer the following as an argument which avoids these problems. 1. Let us call a machine any system which is described by a state evolution function (if it has a continuous state space) or a state transition function (discrete state space). 2. Let us call a description explicit if (a) it is communicable to an arbitrary group of people who know the language in which the description is stated, (b) it is context-independent, i.e. mentions all relevant aspects of the system and its environment to be able to apply it, (c) describes a repeatable process, i.e. whenever the same state occurs, then from that point on the same input sequence will lead to the same output sequence, where "same" is defined as "described by the explicit description as an instance of an input (output) sequence." Laws of nature which describe how a natural process evolves, computer programs, and radio wiring diagrams are explicit descriptions. Now, obviously a machine is an explicitly described system. The essential difference between man and machine I propose is that man possesses the ability to explicate whereas machines do not. The *ability* to explicate is defined as the ability to produce an explicit description of a range of situations which (i.e. the range is) not described explicitly. In principle, one can build a machine which produces explicit descriptions of, say, objects on a conveyor belt. But the set of kinds of objects on the belt would then have to be explicitly described in advance, or at least it would in principle be explicitly describable, even though the description would be large, or difficult to find. the reason for this is that a machine is an explicitly described system, so that, among others, the set of possible inputs is explicitly described. On the other hand, a human being in principle can produce reasonably explicit descriptions of a class of systems which has no sharp boundaries. I think it is this capability which Berke means when he says that human beings can disambiguate whereas algorithmic processes cannot. If the set of inputs to an explication process carried out by a human being is itself not explicitly describable, then humans have a capability which machines don't have. A weak point in this argument is that human beings usually have a hard time in producing totally explicit descriptions; this is why programming is so diffcult. Hence, the qualification "reasonably explicit" above. This does not invalidate the comparison with machines, for a machine built to produce reasonably explicit descriptions would still be an explicitly described system, so that the sets of inputs and outputs would be explicitly described (in particular, the reasonableness of the explicitness of its output would be explicitly described as well). A second argument deriving from the concepts of machine and explicitness focuses on the three components of the concept of explicitness. Suppose that an explication process executed by a human being were explicitly describable. 1. Then it must be communicable; in particular the initial state must be communicable; but this seems one of the most incommunicable mental states there is. 2. It must be context-independent; but especially the initial stage of an explication process seems to be the most context-sensitive process there is. 3. It must be repeatable; but put the same person in the same situation (assuming that we can obliterate the memory of the previous explication of that situation) or put identical twins in the same situation, and we are likely to get different explicit descriptions of that situation. Note that these arguments do not use the concept of ambiguity as defined by Berke and, if valid, apply to any machine, including connection machines. Note also that they are not *proofs*. If they were, they would be explicit descriptions of the relation between a number of propositions, and this would contradict the claim that the explication process has very vague beginnings. Roel Wieringa