Todd, P.M. (1996). Sexual selection and the evolution of learning. In R. Belew and M. Mitchell (Eds.), Adaptive individuals in evolving populations: Models and algorithms (pp. 365-393). Reading, MA: Addison-Wesley.

Abstract

There are two realms in which every living organism must operate. The first is an economic realm of matter and energy, requiring the accrual of resources necessary for an organism's ongoing survival. The second is a genealogical realm of genetic information, requiring appropriate action to ensure an organism's ongoing genetic perpetuation. As Eldredge (1986, p. 351) puts it, "organisms seem to be both energy conversion machines and reproducing `packages' of genetic information." Evolution, as "the primary channel of communication between living systems and their environments" (Plotkin & Odling-Smee, 1979, p. 13), clearly shapes organisms in response to both of these environmental realms. Less well appreciated is the fact that learning, as a secondary means of adapting an organism's internal organization to the external order in the environment, can similarly operate in both domains. In this paper, we will first consider the ways in which learning can evolve through sexual selection, including the sexually selected functions learning may have, the time scales at which these kinds of learning operate, and the differences from naturally selected evolution of learning. We will present a simulation model of the evolution of one particular form of sexually selected learning--parental imprinting--to illustrate these points. We then investigate how learning can affect sexual selection and evolution in turn, leading to such macroevolutionary effects as speciation and runaway selection. This is again illustrated through the simulation study of parental imprinting. Finally, we draw conclusions from this line of inquiry, and describe further directions for the study of sexually selected learning.

See my other publications on Evolution of learning   Mate choice   Sexual selection   



   Back to main page.
   View publications categorized by topic.
   View publication abstracts searchable by keywords