Syntax vs. Semantics

1. Formal Systems

2. On the importance of providing a syntax and a semantics for any KR:
   1. Woods, William A. (1975), "What's in a Link: Foundations for Semantic Networks" (PDF), in D.G. Bobrow & A. Collins (eds.), Representation and Understanding: Studies in Cognitive Science (Orlando, FL: Academic Press): 35-82.
      • Reprinted in:
        Brachman, Ronald J. & Levesque, Hector J. (eds.) (1985), Readings in Knowledge Representation (Los Altos, CA: Morgan Kaufmann): 217-241.

   2. McDermott, Drew (1981), "Artificial Intelligence Meets Natural Stupidity" (PDF), in John Haugeland (ed.), Mind Design: Philosophy, Psychology, Artificial Intelligence (Cambridge, MA: MIT Press, 1981): 143-160.
      • Cartoon on "McDermott's Fallacy"

   3. Far Side cartoon on syntax vs. semantics

3. On the topic of representations not being complete:
   • Smith, Brian Cantwell (1985), "Limits of Correctness in Computers" (PDF), Technical Report CSLI-85-36 (Stanford, CA: Center for the Study of Language and Information).
     • Summary:
       Over the last ten years, the Defense Department has spent many millions of dollars on a new computer technology called `program verification'--a branch of computer science whose business, in its own terms, is to `prove programs correct'. ... What ... does this new technology mean? How good are we at it? ... If it were possible to prove that the programs being written to control automatic launch-on-warning systems were correct, would that mean there could not be a catastrophic accident? ... Do the techniques of program verification hold enough promise so that, if these new systems could all be proven correct, we could all sleep more easily atnight? These are the questions I ... look at in this paper. And my answer ... is no. ... [T]here are fundamental limitations to what can be proven about computers and computer programs. ... Just because a program is `proven correct', ... you cannot be sure that it will do what you intend.

     • Online in PDF; just click on the title.

     • First published in Charles Dunlop & Rob Kling (eds.), Computerization and Controversy (San Diego: Academic Press, 1991): 632-646.

     • Reprinted in Timothy R. Colburn, James H. Fetzer, & Terry L. Rankin (eds.), Program Verification: Fundamental Issues in Computer Science (Dordrecht, Holland: Kluwer Academic Publishers, 1993): 275-293.

4. The work of Alfred Tarski:
   Tarski was the logician who developed the first formal definition of "truth". The first item below is a review of a recent biography of him. The second is a "popular" article he wrote for Scientific American describing the relationships between syntax and semantics, including a sketch of his definition of "truth" and briefly outlining Gödel's incompleteness theorem. Local connection: John Corcoran of the UB PHI department is Tarski's literary executor and editor of a collection of Tarski's papers.
   • Davis, Martin (2005), "The Man Who Defined Truth", American Scientist (March-April).

   • Tarski, Alfred (1969), "Truth and Proof", Scientific American (June): 63-70, 75-77.
     • PDF

5. Goedel's Theorem

6. Google search on Peano's Axioms
   • Hayes, Brian (2001), "How to Count", American Scientist 89(2): 110-114.

7. Smith, Brian Cantwell (1987), "The Correspondence Continuum", Report CSLI-87-71 (Stanford, CA: Center for the Study of Language and Information).

   • Online in PDF; just click on the title.

   • You might also be interested in a couple of my own papers that discuss Smith's views:

     • Rapaport, William J. (1995), "Understanding Understanding: Syntactic Semantics and Computational Cognition" (PDF), in James E. Tomberlin (ed.), AI, Connectionism, and Philosophical Psychology, Philosophical Perspectives Vol. 9 (Atascadero, CA: Ridgeview): 49-88.
       • Online in PDF; just click on the title.

       • Reprinted in Toribio, Josefa, & Clark, Andy (eds.) (1998), Language and Meaning in Cognitive Science: Cognitive Issues and Semantic Theory, Artificial Intelligence and Cognitive Science, Vol. 4: Conceptual Issues (New York: Garland): 73-88.

       • Abstract: John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything makes sense. The question is: What sense does it make?" This essay explores what sense it makes to say that syntax by itself is sufficient for semantics.

     • Rapaport, William J. (2000), "How to Pass a Turing Test: Syntactic Semantics, Natural-Language Understanding, and First-Person Cognition" (PDF), Special Issue on Alan Turing and Artificial Intelligence, Journal of Logic, Language, and Information 9(4): 467-490.
       • Online in PDF; just click on the title.

       • Abstract: A theory of "syntactic semantics" is advocated as a way of understanding how computers can think (and how the Chinese-Room-Argument objection to the Turing Test can be overcome): (1) Semantics, as the study of relations between symbols and meanings, can be turned into syntax--a study of relations among symbols (including meanings)--and hence syntax can suffice for the semantical enterprise. (2) Semantics, as the process of understanding one domain modeled in terms of another, can be viewed recursively: The base case of semantic understanding--understanding a domain in terms of itself--is syntactic understanding. (3) An internal (or "narrow"), first-person point of view makes an external (or "wide"), third-person point of view otiose for purposes of understanding cognition.