Hi everyone, After having read quite a bit about the the C-T Thesis, and its different versions, I'm still somewhat confused on whether it's useable as an in-principle argument for strong AI. Why or why isn't it useable? Since I suspect this is a common question, any good references that you have are appreciated. (Incidentally, I've read Copeland's entry on the C-T Thesis in SEoC (plato.standford.edu).)
I'll edit any answers for SL4's Wiki (http://sl4.org/bin/wiki.pl?HomePage), and thanks very much in advance. Best wishes, Anand _______________________________________________ The following text is from the MIT Encyclopedia of Cognitive Sciences: COMPUTATION AND THE BRAIN Two very different insights motivate characterizing the brain as a computer. The first and more fundamental assumes that the defining function of nervous systems is representational; that is, brain states represent states of some other system the outside world or the body itself-where transitions between states can be explained as computational operations on representations. The second insight derives from a domain of mathematical theory that defines computability in a highly abstract sense. The mathematical approach is based on the idea of a Turing machine. Not an actual machine, the Turing machine is a conceptual way of saying that any well-defined function could be executed, step by step, according to simple "if you are in state P and have input Q then do R" rules, given enough time (maybe infinite time; see COMPUTATION). Insofar as the brain is a device whose input and output can be characterized in terms of some mathematical function- however complicated -then in that very abstract sense, it can be mimicked by a Turing machine. Because neurobiological data indicate that brains are indeed cause-effect machines, brains are, in this formal sense, equivalent to a Turing machine (see CHURCHTURING THESIS). Significant though this result is mathematically, it reveals nothing specific about the nature of mindbrain representation and computation. It does not even imply that the best explanation of brain function will actually be in computational/representational terms. For in this abstract sense, livers, stomachs, and brains-not to mention sieves and the solar system-all compute. What is believed to make brains unique, however, is their evolved capacity to represent the brain's body and its world, and by virtue of computation, to produce coherent, adaptive motor behavior in real time. CHURCH-TURING THESIS Alonzo Church proposed at a meeting of the American Mathematical Society in April 1935, "that the notion of an effectively calculable function of positive integers should be identified with that of a recursive function." This proposal of identifying an informal notion, effectively calculable function, with a mathematically precise one, recursive function, has been called Church's thesis since Stephen Cole Kleene used that name in 1952. Alan TURING independently made a related proposal in 1936, Turing's thesis, suggesting the identification of effectively calculable functions with functions whose values can be computed by a particular idealized computing device, a Turing machine. As the two mathematical notions are provably equivalent, the theses are "equivalent," and are jointly referred to as the Church-Turing thesis. The reflective, partly philosophical and partly mathematical, work around and in support of the thesis concerns one of the fundamental notions of mathematical logic. Its proper understanding is crucial for making informed and reasoned judgments on the significance of limitative results-like G�DEL' S THEOREMS or Church's theorem. The work is equally crucial for computer science, artificial intelligence, and cognitive psychology as it provides also for these subjects a basic theoretical notion. For example, the thesis is the cornerstone for Allen NEWELL's delimitation of the class of physical symbol systems, that is, universal machines with a particular architecture. Newell (1980) views this delimitation "as the most fundamental contribution of artificial intelligence and computer science to the joint enterprise of cognitive science." In a turn that had almost been taken by Turing (1948, 1950), Newell points to the basic role physical symbol systems have in the study of the human mind: "the hypothesis is that humans are instances of physical symbol systems, and, by virtue of this, mind enters into the physical universe . . . this hypothesis sets the terms on which we search for a scientific theory of mind." The restrictive "almost" in Turing's case is easily motivated: he viewed the precise mathematical notion as a crucial ingredient for the investigation of the mind (using computing machines to simulate aspects of the mind), but did not subscribe to a sweeping "mechanist" theory. It is precisely for an understanding of such-sometimes controversial-claims that the background for Church's and Turing's work has to be presented carefully. Detailed connections to investigations in cognitive science, programmatically indicated above, are at the heart of many contributions (cf. for example, COGNITIVE MODELING, COMPUTATIONAL LEARNING THEORY, and COMPUTATIONAL THEORY OF MIND). ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
