The Influence of Learning on Evolution: A Mathematical Framework

Abstract

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

Lamarckian memetic algorithms: local optimum and connectivity structure analysis

“…In the last two decades, a few studies to enhance the understandings of Baldwinian MAs (26)(27)(28)(29) have been reported. However, to the best of our knowledge little progress on study of Lamarckian MA in non-linear programming has been made so far (30)(31)(32) with few exceptions (33).…”

New thinking about biological evolution

“…The hypothesis of the adaptability driver has been repeatedly modelled, both analytically (Ancel, , ; Mills & Watson, ; Borenstein, Meilijson & Ruppin, ; Borenstein, Feldman & Aoki, ; Paenke, Kawecki & Sendhoff, ) and by simulation (Hinton & Nowlan, ; Nolfi, Parisi & Elman, ; Suzuki & Arita, ; Red'ko, Mosalov & Prokhorov, ). The outcome of this theoretical activity has been variable, sometimes supporting the adaptability driver hypothesis and sometimes not.…”

“…Paenke et al . () proposed a general framework that explained both effects. Spontaneously expressing a behaviour that had been learned in previous generations could be costly if it meant that the animal lost all of its ability to learn.…”

“…Emphasis was placed on how particular behaviour patterns initially acquired by learning could be expressed spontaneously without learning in the course of subsequent evolution. Recent developments initiated by the work of Hinton & Nowlan () have shifted the focus to other issues, such as the way in which plasticity can accelerate the rate at which challenges set by the environment can be met (Fontanari & Meir, ; Paenke et al ., ), the advantages of plasticity in a changing environment (Ackley & Littman, ; Anderson, ; Bergman & Feldman, ; Ancel, ; Dopazo et al ., ; Suzuki & Arita, ; Red'ko et al ., ; Borenstein et al ., ; Pfennig & McGee, ), and the conditions in which plasticity might slow down evolution (Ancel, ; Paenke et al ., ).…”

Imitation tendencies of local search schemes in baldwinian evolution

“…The guiding effect of Baldwinian learning in the search was first verified by Hinton and Nowlan [8]. In the following years researches were taken on the characteristics in the process of Baldwinian evolution [23,15,22,14], the interaction of learning, evolution and development [4,5,6], and the fact that Baldwinian learning can also be hiding [20,21]. Furthermore there are works trying to combine Baldwinian and Lamarckian evolution [3,9,2].…”