The Limits Of Mathematics (discrete Mathematics And Theoretical Computer Science)

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This book is the final version of a course on algorithmic information theory and the epistemology of mathematics and physics. It discusses Einstein and Goedel's views on the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical. There is a foreword by Cris Calude of the University of Auckland, and supplementary material is available at the author's web site. The special feature of this book is that it presents a new "hands on" didatic approach using LISP and Mathematica software. The reader will be able to derive an understanding of the close relationship between mathematics and physics. "The Limits of Mathematics is a very personal and idiosyncratic account of Greg Chaitin's entire career in developing algorithmic information theory. The combination of the edited transcripts of his three introductory lectures maintains all the energy and content of the oral presentations, while the material on AIT itself gives a full explanation of how to implement Greg's ideas on real computers for those who want to try their hand at furthering the theory." (John Casti, Santa Fe Institute)

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arXiv:chao-dyn/9407003v1 7 Jul 1994 THE LIMITS OF MATHEMATICS G. J. Chaitin IBM, P O Box 704 Yorktown Heights, NY 10598 [email protected] Draft July 7, 1994 To Fran¸coise Preface In a remarkable development, I have constructed a new definition for a self-delimiting universal Turing machine (UTM) that is easy to program and runs very quickly. This provides a new foundation for algorithmic information theory (AIT), which is the theory of the size in bits of programs for self-delimiting UTM’s. Previously, AIT had an abstract mathematical quality. Now it is possible to write down executable programs that embody the constructions in the proofs of theorems. So AIT goes from dealing with remote idealized mythical objects to being a theory about practical down-to-earth gadgets that one can actually play with and use. This new self-delimiting UTM is implemented via an extremely fast LISP interpreter written in C. The universal Turing machine U is written in this LISP. This LISP also serves as a very high-level assembler to put together binary programs for U. The programs that go into U, and whose size we measure, are bit strings. The output from U, on the other hand, consists of a single LISP S-expression, in the case of finite computations, and of an infinite set of these S-expressions, in the case of infinite computations. The LISP used here is based on the version of LISP that I used in my book Algorithmic Information Theory, Cambridge University Press, 1987. The difference is that a) I have found a self-delimiting way to give binary data to LISP programs, and b) I have found a natural way to handle unending computations, which is what formal axiomatic systems are, in LISP. Using this new software, as well as the latest theoretical ideas, it is now possible to give a self-contained “hands on” course presenting very concretely my latest proofs of my two fundamental informationv vi theoretic incompleteness theorems. The first of these theorems states that an N-bit formal axiomatic system cannot enable one to exhibit any specific object with program-size complexity greater than N + c. The second of these theorems states that an N-bit formal axiomatic system cannot enable one to determine more than N + c′ scattered bits of the halting probability Ω. Most people believe that anything that is true is true for a reason. These theorems show that some things are true for no reason at all, i.e., accidentally, or at random. The latest and I believe the deepest proofs of these two theorems were originally presented in m