Transient phenomena in learning and evolution: genetic assimilation and genetic redistribution

Wiles, Janet, Watson, James, Tonkes, Bradley and Deacon, Terrence (2005) Transient phenomena in learning and evolution: genetic assimilation and genetic redistribution. Artificial Life, 11 1-2: 177-188. doi:10.1162/1064546053279026

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Author Wiles, Janet
Watson, James
Tonkes, Bradley
Deacon, Terrence
Title Transient phenomena in learning and evolution: genetic assimilation and genetic redistribution
Journal name Artificial Life   Check publisher's open access policy
ISSN 1064-5462
1530-9185
Publication date 2005-01-01
Sub-type Article (original research)
DOI 10.1162/1064546053279026
Open Access Status File (Publisher version)
Volume 11
Issue 1-2
Start page 177
End page 188
Total pages 12
Editor M. A. Bedau
Place of publication Boston, Massachusetts, United states
Publisher MIT Press
Collection year 2005
Language eng
Abstract Deacon has recently proposed that complexes of genes can be integrated into functional groups as a result of environmental changes that mask and unmask selection pressures. For example, many animals endogenously synthesize ascorbic acid (vitamin C), but anthropoid primates have only a nonfunctional version of the crucial gene for this pathway. It is hypothesized that the loss of functionality occurred in the evolutionary past when a diet rich in vitamin C masked the effect of the gene, and its loss effectively trapped the animals in a fruit-eating lifestyle. As a result, the complex of abilities that support this lifestyle were evolutionarily bound together, forming a multilocus complex. In this study we use evolutionary computation simulations to explore the thesis that masking and unmasking can transfer dependence from one set of genes to many sets, and thereby integrate the whole complex of genes. We used a framework based on Hinton and Nowlan's 1987 simulation of the Baldwin effect. Additional gene complexes and an environmental parameter were added to their basic model, and the fitness function extended. The simulation clearly demonstrates that the genetic redistribution effect can occur in silico, showing an initial advantage of endogenously synthesized vitamin C, followed by transfer of the fitness contribution to the complex of genes that together allow the acquisition of vitamin C from the environment. As is well known in the modeling community, the Baldwin effect only occurs in simulations when the population of agents is "poised on the brink" of discovering the genetically specified solution. Similarly, the redistribution effect occurs in simulations under specific initial conditions: too little vitamin C in the environment, and its synthesis it is never fully masked; too much vitamin C, and the abilities required to acquire it are not tightly integrated. The Baldwin effect has been hypothesized as a potential mechanism for developing language-specific adaptations like innate universal grammar and other highly modular capacities. We conclude with a discussion of the relevance of genetic assimilation and genetic redistribution to the evolution of language and other cognitive adaptations.
Keyword Baldwin effect
Genetic assimilation
Genetic redistribution
Genetic variation
Adaptation
Evolutionary computation
References Ackley, D. H., & Littman, M. L. (1992). Interactions between learning and evolution. In C. G. Langton, C. Taylor, C. D. Farmer, & S. Rasmussen (Eds.), Artificial Life II (pp. 487-509). Reading, MA: Addison-Wesley. 2. Baldwin, J. M. (1896, 1996). A new factor in evolution. American Naturalist, 30, 441-451. Reproduced in R. K. Belew, & M. Mitchell (Eds.), Adaptive individuals in evolving populations. Reading, MA: Addison-Wesley. 3. Belew, R. K. (1990). Evolution, learning and culture: Computational metaphors for adaptive search. Complex Systems, 4(1), 11-49. 4. Cohen, J., & Stewart, I. (1994). The collapse of chaos. London: Penguin. 5. Chalmers, D. (1990). The evolution of learning: An experiment in genetic connectionism. In D. S. Touretsky, J. L. Elman, T. J. Sejnowski, & G. E. Hinton (Eds.), Proceedings of the 1990 Connectionist Summer School (pp. 81-90). San Mateo, CA: Morgan Kaufmann. 6. Deacon, T. W. (2003). Multilevel selection in a complex adaptive system: The problem of language origins. In B. H. Weber, & D. J. Depew (Eds.), Evolution and learning: The Baldwin effect reconsidered. Cambridge, MA: MIT Press. 7. Frazzetta, T. H. (1975). Complex adaptations in evolving populations. Sunderland, MA: Sinauer. 8. French, R. M., & Messinger, A. (1994). Genes, phenes and the Baldwin effect: Learning and evolution in a simulated population. In R. Brooks & P. Maes (Eds.), Artificial Life IV. Cambridge, MA: MIT Press. 9. Harvey, I. (1993). The puzzle of the persistent question marks: A case study of genetic drift.In S. Forrest ( Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms. San Mateo, CA: Morgan Kaufmann. 10. Hinton, G. E., & Nowlan, S. J. (1987). How learning can guide evolution. Complex Systems, 1, 495-502. 11. Mayley, G. (1996). The evolutionary cost of learning. In P. Maes, M. J. Mataric, J.-A. Meyer, J. Pollack, and S. W. Wilson (Eds.), From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior. (pp. 458-467). Cambridge, MA: MIT Press. 12. Mitchell, M. (1996). An introduction to genetic algorithms. Cambridge, MA: MIT Press. 13. Morgan, C. L. (1896). On modification and variation. Science, 99, 733-740. 14. Nishikimi, M., Fukuyama, R., Minoshoma, S., Shimizu, N., & Yagi, K. (1994). Cloning and chromosomal mapping of the human nonfunctional gene for L-gulono-g-lactone oxidase, the enzyme for L-ascorbic acid biosynthesis missing in man. Journal of Biological Chemistry, 269, 13685-13688. 15. Nolfi, S., & Floreano, D. (2000). Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines. Cambridge, MA: MIT Press. 16. Pinker, S. (1997). How the mind works. London: Penguin. 17. Turney, P., Whitley, D., & Anderson, R. (Eds.) (1996). Evolution, learning and instinct: 100 years of the Baldwin effect. Cambridge, MA: MIT Press. 18. Watson, J., Geard, N. & Wiles, J. (2002). Stability and task complexity: A neural network model of evolution and learning. In R. K. Standish, M. A. Bedau, & H. A. Abbass (Eds.), Proceedings of the Eighth International Conference on Artificial Life (pp. 153-156). 19. Watson, J., & Wiles, J. (2002). The rise and fall of learning: A neural network model of the genetic assimilation of acquired traits. In X. Yao ( Ed.), Proceedings of the 2002 Congress on Evolutionary Computation (pp. 600-605). Piscataway, NJ: IEEE. 20. Wiles, J., Schulz, R., Bolland, S., & Hallinan, J. (2001). Probing the persistent question marks. In L. Spector, E. Goodman, A. Wu, W. B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, & E. Burke (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001) (pp. 710-717). San Mateo, CA: Morgan Kaufmann. 21. Wiles, J., Schulz, R., Bolland, S., Tonkes, B., & Hallinan, J. (2001). Selection procedures for module discovery: Exploring evolutionary algorithms for cognitive science. In J. D. Moore, and K. Stenning, (Eds.), Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society (pp. 1124-1129). Mahwah, NJ: Erlbaum.
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Created: Tue, 03 Jan 2006, 10:00:00 EST by Janet Wiles on behalf of School of Information Technol and Elec Engineering