Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-26T17:01:43.917Z Has data issue: false hasContentIssue false

Objectivity, Information, and Maxwell's Demon

Published online by Cambridge University Press:  01 January 2022

Abstract

This paper examines some common measures of complexity, structure, and information, with an eye toward understanding the extent to which complexity or information-content may be regarded as objective properties of individual objects. A form of contextual objectivity is proposed which renders the measures objective, and which largely resolves the puzzle of Maxwell's Demon.

Type
Topics in Philosophy of Physics
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Thanks to Jos Uffink and Janneke van Lith–van Dis for helpful discussions.

References

Angrist, Stanley W., and Hepler, Loren G. (1967), Order and Chaos. New York: Basic Books.Google Scholar
Borges, Jorge Luis (1964), “The Library of Babel”, in Yates, Donald A. and Irby, James E. (eds.), Labyrinths: Selected Stories and Other Writings. New York: New Directions, pp. 5158.Google Scholar
Caves, Carlton (1990), “Entropy and Information: How Much Information is Needed to Assign a Probability”, in Zurek, Wojciech (ed.), Complexity, Entropy and the Physics of Information, SFI Studies in the Science of Complexity, Vol. VIII, Reading, PA: Addison-Wesley, pp. 91113.Google Scholar
Chaitin, Gregory (1966), “On the Length of Programs for Computing Binary Sequences”, On the Length of Programs for Computing Binary Sequences 13:547569.Google Scholar
Cover, Thomas, and Thomas, Joy (1991), Elements of Information Theory. New York: John Wiley and Sons.CrossRefGoogle Scholar
Dennett, Daniel (1991), “Real Patterns”, Real Patterns 88:2751.Google Scholar
Earman, John, and Norton, John (1998), “Exorcist XIV: The Wrath of Maxwell's Demon, part I—from Maxwell to Szilard”, Exorcist XIV: The Wrath of Maxwell's Demon, part I—from Maxwell to Szilard 29:435471.Google Scholar
Earman, John, and Norton, John (1999), “Exorcist XIV: The Wrath of Maxwell's Demon, part II—from Szilard to Landauer and Beyond”, Exorcist XIV: The Wrath of Maxwell's Demon, part II—from Szilard to Landauer and Beyond 30:140.Google Scholar
Grad, Harold (1961), “The Many Faces of Entropy”, The Many Faces of Entropy 14:323354.Google Scholar
Jaynes, Edwin T. (1965), Thermodynamics, unpublished, available at http://bayes.wustl.edu/etj/thermo.html.Google Scholar
Jaynes, Edwin T. (1992), “The Gibbs paradox”, in Maximum-Entropy and Bayesian Methods. Dordrecht: Kluwer.Google Scholar
Kolmogorov, Andrei (1965), “Three Approaches to the Quantitative Definition of Information”, Three Approaches to the Quantitative Definition of Information 1:47.Google Scholar
Leff, Harvey, and Rex, Andrew (1990), Maxwell's Demon: Entropy, Information, Computing. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Lloyd, Elisabeth (1995), “Objectivity and the Double Standard for Feminist Epistemologies”, Objectivity and the Double Standard for Feminist Epistemologies 194:351381.Google Scholar
Maxwell, James Clerk (1871), Theory of Heat. London: Longmans, Green, and Co.Google Scholar
Nielsen, Michael A., and Chuang, Isaac L. (2000), Quantum Computation and Quantum Information. Cambridge: Cambridge University Press.Google Scholar
Corporation, Rand (1955), A Million Random Digits with 100,000 Normal Deviates. Glencoe, IL: The Free Press.Google Scholar
Shannon, Claude (1948), “A Mathematical Theory of Communication”, A Mathematical Theory of Communication 27:379423, 623–656.Google Scholar
Solomonoff, Ray (1964), “A Formal Theory of Inductive Inference”, A Formal Theory of Inductive Inference 7:122, 224–254.Google Scholar
Uffink, Jos (2001), “Bluff Your Way in the Second Law of Thermodynamics”, Bluff Your Way in the Second Law of Thermodynamics 32:305394.Google Scholar