eprintid: 7047
rev_number: 27
eprint_status: archive
userid: 8
dir: disk0/00/00/70/47
datestamp: 2013-04-18 13:47:05
lastmod: 2016-08-26 01:31:03
status_changed: 2013-04-18 13:47:05
type: book
metadata_visibility: show
creators_name: G J , Chaitin
title: ALGORITHMIC INFORMATION THEORY
ispublished: pub
subjects: ebok_algo
divisions: a-buku
full_text_status: restricted
keywords: ALGORITHMIC, INFORMATION, THEORY
abstract: More than half a century has passed since the famous papers Godel (1931) and Turing (1937) that shed so much light on the foundations of mathematics, and that simultaneously promulgated mathematical formalisms for specifying algorithms, in one case via primitive recursive function denitions, and in the other case via Turing machines. The development of computer hardware and software technology during this period has been phenomenal, and as a result we now know much better how to do the high-level functional programming of Godel, and how to do the low-level machine language programming found in Turing's paper. And we can actually run our programs on machines and debug them, which Godel and Turing could not do.
I believe that the best way to actually program a universal Turing machine is John McCarthy's universal function EVAL. In 1960 Mc- Carthy proposed LISP as a new mathematical foundation for the theory of computation [McCarthy (1960)]. But by a quirk of fate LISP has largely been ignored by theoreticians and has instead become the standard programming language for work on articial intelligence. I believe that pure LISP is in precisely the same role in computational mathematics that set theory is in theoretical mathematics, in that it provides a beautifully elegant and extremely powerful formalism which
enables concepts such as that of numbers and functions to be dened from a handful of more primitive notions.
date: 2009-03-10
date_type: published
series: Buku
publication: September 30, 1997
volume: Vol.1
number: No. 1
publisher: Yorktown Heights
pages: 236
refereed: TRUE
citation:   G J , Chaitin  (2009) ALGORITHMIC INFORMATION THEORY.    Buku, Vol.1  (No. 1).  Yorktown Heights.      
document_url: https://digilib.uin-suka.ac.id/id/eprint/7047/1/Algorithmic%20Information%20Theory.pdf