A Primer on the Tools and Concepts of Comutable Economics.

Computability theory came into being as a result of Hilbert?s attempts to meet Brouwer?s challenges, from an intuitionistc and constructive standpoint, to formalism as a foundation for mathematical practice. Viewed this way, con- structive mathematics should be one vision of computability theory. However, there are fundamental di¤erences between computability theory and construc- tive mathematics: the Church-Turing thesis is a disciplining criterion in the former and not in the latter; and classical logic - particularly, the law of the excluded middle - is not accepted in the latter but freely invoked in the former, especially in proving universal negative propositions. In Computable Economics an eclectic approach is adopted where the main criterion is numerical content for economic entities. In this sense both the computable and the constructive traditions are freely and indiscriminately invoked and utilised in the formaliza- tion of economic entities. Some of the mathematical methods and concepts of computable economics are surveyed in a pedagogical mode. A digital economy is considered embedded in an information society and speculative methodolog- ical, epistemological and ontological notes suggest a theory of the information society.

[1]  W. Feller,et al.  An Introduction to Probability Theory and Its Application. , 1951 .

[2]  T. Sargent,et al.  Recursive Macroeconomic Theory , 2000 .

[3]  Anthony J. G. Hey,et al.  Feynman Lectures on Computation , 1996 .

[4]  A. Bountis Dynamical Systems And Numerical Analysis , 1997, IEEE Computational Science and Engineering.

[5]  Oliver Aberth,et al.  Computable analysis , 1980 .

[6]  Donald E. Knuth,et al.  Algorithmic Thinking and Mathematical Thinking , 1985 .

[7]  Simon A. Levin,et al.  Complex adaptive systems: Exploring the known, the unknown and the unknowable , 2002 .

[8]  R. L. Goodstein A text-book of mathematical analysis : the uniform calculus and its applications , 1949 .

[9]  G. Kreisel A Notion of Mechanistic Theory , 1974 .

[10]  I. Fisher Mathematical Investigations in the Theory of Value and Prices , 1893 .

[11]  V. Smith Microeconomic Systems as an Experimental Science , 1982 .

[12]  Ernst Specker,et al.  Nicht konstruktiv beweisbare Sätze der Analysis , 1949, Journal of Symbolic Logic.

[13]  M. Osborne Brownian Motion in the Stock Market , 1959 .

[14]  Finn E. Kydland,et al.  Business cycles: real facts and a monetary myth , 1990 .

[15]  Howard Raiffa,et al.  Games and Decisions: Introduction and Critical Survey. , 1958 .

[16]  L. Bachelier,et al.  Theory of Speculation , 1964 .

[17]  R. Feynman Simulating physics with computers , 1999 .

[18]  Peter S. Albin,et al.  Barriers and Bounds to Rationality , 1998 .

[19]  Brian E. Carpenter,et al.  A. M. Turing's ACE Report of 1946 and Other Papers , 1986 .

[20]  Vernon L. Smith,et al.  EXPERIMENTAL MARKET ECONOMICS , 1992 .

[21]  Newton C. A. da Costa,et al.  The Incompleteness of Theories of Games , 1998, J. Philos. Log..

[22]  A. N. Kolmogorov Combinatorial foundations of information theory and the calculus of probabilities , 1983 .

[23]  J. Barkley Rosser,et al.  DYNAMICS OF MARKETS : ECONOPHYSICS AND FINANCE , 2006 .

[24]  Kumaraswamy Velupillai Computability, complexity and constructivity in economic analysis , 2005 .

[25]  E. Phelps Microeconomic Foundations of Employment and Inflation Theory , 1970 .

[26]  G. Hardy A Course of Pure Mathematics , 1910 .

[27]  R. Goodwin Dynamical Coupling with Especial Reference to Markets Having Production Lags , 1947 .

[28]  Klaus Weihrauch,et al.  Computable Analysis: An Introduction , 2014, Texts in Theoretical Computer Science. An EATCS Series.

[29]  B. Hayes,et al.  A Lucid Interval , 2003, American Scientist.

[30]  Lenore Blum,et al.  Complexity and Real Computation , 1997, Springer New York.

[31]  J. E. Cairnes Some Leading Principles of Political Economy Newly Expounded , 1967 .

[32]  J. Hartmains,et al.  Computing the future , 1992 .

[33]  Donald E. Knuth,et al.  Algorithms in Modern Mathematics and Computer Science , 1979, Lecture Notes in Computer Science.

[34]  A. Opstal Dynamic Patterns: The Self-Organization of Brain and Behavior , 1995 .

[35]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[36]  R. Thaler Advances in behavioral finance , 1995 .

[37]  P. Lorenzen Differential and integral;: A constructive introduction to classical analysis , 1971 .

[38]  Deterministic Chaos in Economics: An Occurrence in Axiomatic Utility Theory , 1990 .

[39]  S. Smale Dynamics in General Equilibrium Theory , 1976 .

[40]  Gavan Lintern,et al.  Dynamic patterns: The self-organization of brain and behavior , 1997, Complex.

[41]  A. M. Turing,et al.  The chemical basis of morphogenesis , 1952, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences.

[42]  E. Chamberlin,et al.  An Experimental Imperfect Market , 1948, Journal of Political Economy.

[43]  R. Courant Differential and Integral Calculus , 1935 .

[44]  M. Osborne The Stockmarket and Finance from a Physicist's Viewpoint , 1996 .

[45]  Christos H. Papadimitriou,et al.  On the Complexity of the Parity Argument and Other Inefficient Proofs of Existence , 1994, J. Comput. Syst. Sci..

[46]  Donald E. Knuth,et al.  Algorithms in Modern Mathematics and Computer Science, Proceedings, Urgench, Uzbek SSR, USSR, September 16-22, 1979 , 1981, Algorithms in Modern Mathematics and Computer Science.

[47]  O. Bunke Feller, F.: An Introduction to Probability Theory and its Applications, Vol. II, John Wiley & Sons, Inc., New York‐London‐Sydney, 1966. XVIII + 626 S., 3 Abb., 2 Tab., Preis $ 12,00 , 1969 .

[48]  J. Barkley Rosser,et al.  Logic for mathematicians , 1978 .

[49]  T. Koopmans Three Essays on the State of Economic Science , 1958 .

[50]  P. O’Gorman,et al.  Theories and Things , 1986 .

[51]  Vernon L. Smith,et al.  Microeconomic Systems as an Experimental Auction Market , 1982 .