Abstract
What permits some systems to evolve and adapt more effectively than others? Gell-Mann [3] has stressed the importance of “compression” for adaptive complex systems. Information about the environment is not simply recorded as a look-up table, but is rather compressed in a theory or schema. Several conjectures are proposed: (I) compression aids in generalization; (II) compression occurs more easily in a “smooth”, as opposed to a “rugged”, string space; and (III) constraints from compression make it likely that natural languages evolve towards smooth string spaces. We have been examining the role of such compression for learning and evolution of formal languages by artificial agents. Our system does seem to conform generally to these expectations, but the tradeoffs between compression and the errors that sometimes accompany it need careful consideration.
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References
N. Chomsky. Aspects of the Theory of Syntax. MIT Press, Cambridge, MA, 1965.
N. Chomsky. The Minimalist Program. MIT Press, Cambridge, MA, 1995.
M. Gell-Mann. Talk at Santa Fe Institute, January 9 1990.
E. M. Gold. Complexity of automaton identification from given data. Information and Control, 37:302–320, 1978.
P. Grünwald. A minimum description length approach to grammar inference. In G. Scheler S. Wermter, E. Riloff, editor, Symbolic, Connectionist and Statistical Approaches to Learning for Natural Language Processing, LNCS #1040. Springer-Verlag, Berlin, 1996.
T. Hashimoto. Usage-based structuralization of relationships between words. In P. Husbands and I. Harvey, editors, Fourth European Conference on Artificial Life, pages 483–492, Cambridge, MA, 1997. MIT Press.
J.E. Hopcroft and J.D. Ullman. Introduction to Automata theory, Languages and Computation. Addison Wesley, Reading, MA, 1979.
S.A. Kauffman. The Origins of Order: Self-Organization in Evolution. Oxford University Press, New York, 1993.
M.J. Kearns and U.V. Vazirani. An Introduction to Computational Learning Theory. MIT Press, Cambridge, MA, 1994.
S. Kirby. Syntax without natural selection: How compositionality emerges from vocabulary in a population of learners. Unpublished ms., 1999.
S. Kirby and J. Hurford. Learning, culture and evolution in the origin of linguistic constraints. In P. Husbands and I. Harvey, editors, Fourth European Conference on Artificial Life, pages 493–502, Cambridge, MA, 1997. MIT Press.
M. Li and P. Vitányi. Minimum description length induction, bayesianism and kolmogorov complexity. In 1998 IEEE International Symposium on Information Theory, MIT, Cambridge, 1998.
J. A. Moore. Science as a Way of Knowing. Harvard University Press, Cambridge, MA, 1993.
P. Niyogi and R.C. Berwick. The logical problem of language change. Technical Report A. I. Memo No. 1516, MIT Artificial Intelligence Laboratory, July 1995.
C.H. Papadimtriou and M. Sideri. On the evolution of easy instances. Unpublished manuscript, 1998.
J. Rissanen and E. Ristad. Language acquisition in the MDL framework. In E. Ristad, editor, Language Computations. American Mathematical Society, Philadelphia, PA, 1994.
K. Sayood. Introduction to Data Compression. Morgan Kauffman, San Francisco, CA, 1996.
L. B. Slobodkin. Simplicity and Complexity in Games of the Intellect. Harvard University Press, Cambridge, MA, 1992.
E. Stabler. Computational Minimalism: Acquiring and Parsing Languages with Movement. Basil Blackwell, Oxford, 1999.
V.N. Vapnik. Statistical Learning Theory. Wiley, NY, 1998.
J. Weber and C. Wong. Mutation of human short tandem repeats. Human Molecular Genetics, 2(8):1123–1128, 1993.
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Teal, T., Albro, D., Stabler, E., Taylor, C.E. (1999). Compression and Adaptation. In: Floreano, D., Nicoud, JD., Mondada, F. (eds) Advances in Artificial Life. ECAL 1999. Lecture Notes in Computer Science(), vol 1674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48304-7_93
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DOI: https://doi.org/10.1007/3-540-48304-7_93
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