Rethinking Innateness presents a progression, from issues typically considered part of developmental psychology, through consideration of the processes of neurogenesis, to a consideration of the process of biological development more generally. This talk continues that progression to investigate the role development plays in evolution, and vice versa.
Since the focus heretofore has been on processes by which individuals change, "innate" characteristics have been considered the fixed, invariant traits which constrain the extend of such change. But from an evolutionary perspective, the innate too is changing. This type of change typically takes much longer and involves entire species, but is equally adaptive. Of course the most interesting issues arise as we consider how the processes of individual- and population-based change interact.
Consistent with Rethinking Innateness's approach, our means of analysis will be computational models. Connectionist, neural network models will be discussed as elements of more inclusive models, of the sort promised by this book's preface:
[B]y using connectionist models together with genetic algorithms and artificial life models, it is possible to study within one and the same simulation evolutionary change at the level of populations of neural networks, maturation and learning in individual neural networks, and the interactions between the two. (p. xiii)
Two background readings are recommended to students in the class. The first is the introductory chapter of Adaptive Individuals in Evolving Populations, a book I editted with Melanie Mitchell. This book is centrally concerned with interactions between adaptation at the individual and population levels, and the first chapter provides a good overview of many of the issues; this chapter is available as an HTML document. The second reading is a manuscript, "Interacting models of evolution, learning and maturation" prepared by Domenico Parisi and I and originally intended for inclusion in Rethinking Innateness; this chapter is available as a Postscript file.