Evolvability

Journal of the ACM

Volumn 56, Issue 1, 2009, Pages

  Valiant, Leslie G ^a  

^a HARVARD UNIVERSITY   (United States)

Author keywords

Evolvable; PAC learning; SQ learning

Indexed keywords

BIOLOGICAL EVOLUTIONS; COMPLEX MECHANISMS; COMPUTATIONAL LEARNING; DARWIN'S THEORIES; DARWINIAN EVOLUTIONS; EVOLUTIONARY STAGES; EVOLVABILITY; EVOLVABLE; FUNCTION CLASS; LIVING ORGANISMS; NATURAL SELECTIONS; PAC LEARNING; PARITY FUNCTIONS; POPULATION SIZES; SINGLE STAGES; SQ LEARNING; TECHNICAL SENSE; TIME PERIODS; UNIFORM DISTRIBUTIONS;

BOOLEAN FUNCTIONS; DISTRIBUTION FUNCTIONS; FUNCTIONS; POPULATION STATISTICS; PROBABILITY DENSITY FUNCTION; PROGRAMMING THEORY; TARGETS;

EDUCATION;

EID: 60349123335     PISSN: 00045411     EISSN: 1557735X     Source Type: Journal    
DOI: 10.1145/1462153.1462156     Document Type: Article

References (30)

1. BÄCK, T., FOGEL, D. B., AND MICHALEWISZ, Z. (EDS.). 1997. Handbook of Evolutionary Computation. Oxford Univ. Press, Oxford, UK.
2. BERJERANO, G. PHEASANT, M., MAKUNIN, I., STEPHEN, S., KENT, W. J., MATTICK, J. S., AND HAUSSLER, D. 2004. Ultraconserved elements in the human genome. Science 304, 1321-1325.
3. BLUMER, A., EHRENFEUCHT, A., HAUSSLER, D., AND WARMUTH, M. K. 1989. Learnability and the Vapnik Chervonenkis dimension. J. ACM 36, 4, 929-965.
4. BURGER, R. 2000. The Mathematical Theory of Selection, Recombination, and Mutation. Wiley, Chichester, UK.
5. DARWIN, C. 1859. On the Origin of Species by Means of Natural Selection. John Murray, London, UK.
6. DERMITZAKIS, E. T., RAYMOND, A., AND ANTONARAKIS, S. E. 2005. Conserved nongenic sequences-An unexpected feature of mammalian genomes. Nat. Rev. Genet. 6, 2(Feb.), 151-157.
7. DRAKE, J. W., CHARLESWORTH, B., CHARLESWORTH, D., AND CROW, F. J. 1998. Rates of spontaneous mutation. Genetics 148, 1667-1686.
8. EHRENFEUCHT, A., HAUSSLER, D., KEARNS, M., AND VALIANT, L. G. 1989. A general lower bound on the number of examples needed for learning. Inf. Comput. 82, 2, 247-261.
9. FELDMAN, V. 2008. Evolvability from learning algorithms. In Proceedings of the 40th ACM Symposium on Theory of Computing. ACM, New York, 619-628.
10. FISCHER, P., AND SIMON, H. U. 1992. On learning ring-sum expressions. SIAM J. Comput. 21, 1, 181-192.
11. FISHER, R. A. 1930. The Genetical Theory of Natural Selection. Oxford Univ. Press, Oxford, UK.
12. GAREY, M. R., AND JOHNSON, D. S. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, San Francisco, CA.
13. HELMBOLD, D., SLOAN, R., AND WARMUTH, M. K. 1992. Learning integer lattices. SIAM J. Computing 21, 2, 240-266.
14. HOEFFDING, W. 1963. Probability inequalities for suras of bounded random variables. J. Amer. Stat. Assoc. 58, 13.
15. KEARNS, M. 1998. Efficient noise tolerant learning from statistical queries. J. ACM 45, 6, 983-1006.
16. KEARNS, M., AND VALIANT, L. G. 1994. Cryptographic limitations on learning Boolean formulae. J. ACM 41, 1, 67-95.
17. KEARNS, M., AND VAZIRANI, U. 1994. An Introduction to Computational Learning Theory. MIT Press, Cambridge, MA.
18. KIMURA, M. 1968. Evolutionary rate at the molecular level. Nature 217, 624-626.
19. KUMAR, S., AND SUBRAMANIAN, S. 2002. Mutation rates in mammalian genomes. Proc. Nat. Acad. Sci. 99, 803-808.
20. MAYNARD-SMITH, J. 1982. Evolution and the Theory of Games. Cambridge Univ. Press, Cambridge, UK.
21. PAPADIMITRIOU, C. H. 1994. Computational Complexity. Addison-Wesley, Reading, MA.
22. PITT, L., AND VALIANT, L. G. 1988. Computational limitations on learning from examples. J. ACM 35, 4, 965-984.
23. ROFF, D. A. 1997. Evolutionary Quantitative Genetics. Chapman & Hall, New York.
24. ROS, J. P. 1993. Learning Boolean functions with genetic algorithms: A PAC analysis. In Foundations of Genetic Algorithms, L. D. Whitley, Ed., Morgan-Kaufmann, San Mateo, CA, 257-275.
25. VALIANT, L. G. 1984. A theory of the learnable. Comm. ACM, 27, 11, 1134-1142.
26. VALIANT, L. G. 2000. Robust logics. Artif. Intell. J. 117, 231-253.
27. VALIANT, L. G. 2006. Knowledge infusion. In Proceedings of the 21st National Conference on Artificial Intelligence. (AAAI'06). 1546-1551.
28. WAGNER, G. P., AND ALTENBERG, L. 1996. Complex adaptations and the evolution of evolvability. Evolution 50, 3, 967-976.
29. WEGENER, I. 2001. Theoretical aspects of evolutionary algorithms. In Proceedings of the 28th International Colloquium on Automata, Languages and Programming. Lecture Notes in Computer Science, vol. 2076, Springer-Verlag, Berlin, Germany, 64-78.
30. WRIGHT, S. 1968-1978. Evolution and the Genetics of Populations, A Treatise. University of Chicago Press, Chicago, IL.