Development and the Baldwin effect

Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds

Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.

A Study on Computational Efficiency and Plasticity in Baldwinian Learning

Baldwinian evolution is a hybridization of populationbased search and local refinements. Unlike in Lamarckian evolution, selection is made based on fitness improved in local refining, but refined traits are not known to offspring. For potential use in computational applications, we must investigate the Baldwinian evolutionmechanism, in term of computational cost and fitness improvement. In this paper, a set of experiments is presented, to find what is produced in Baldwinian learning. We found that, on the static landscapes involved, learning cost is paid to maintain a certain level of potential to reach good solutions, rather than to further explore on the landscape. Plasticity codes in genotypes can help in selecting appropriate parts to refine and improve search performance. However, this improvement remains limited because no learned traits are passed on, and does not enable exploration far beyond parents.

The influence of learning on evolution: a mathematical framework

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.

The dynamic changes in roles of learning through the Baldwin effect

The interaction between evolution and learning called the Baldwin effect is a two-step evolutionary scenario caused by the balances between benefit and cost of learning in general. However, little is known about the dynamic evolution of these balances in complex environments. Our purpose is to give a new insight into the benefit and cost of learning by focusing on the quantitative evolution of phenotypic plasticity under the assumption of epistatic interactions. For this purpose, we have constructed an evolutionary model of quantitative traits by using an extended version of Kauffman's NK fitness landscape. Phenotypic plasticity is introduced into our model; whether each phenotype is plastic or not is genetically defined, and plastic phenotypes can be adjusted by learning. The simulation results clearly show that drastic changes in roles of learning cause three-step evolution through the Baldwin effect and also cause the evolution of genetic robustness against mutations. We also conceptualize four different roles of learning by using a hill-climbing image of a population on a fitness landscape.

The effect of phenotypic plasticity on evolution in multipeaked fitness landscapes

When facing the challenge of developing an individual that best fits its environment, nature demonstrates an interesting combination of two fundamentally different adaptive mechanisms: genetic evolution and phenotypic plasticity. Following numerous computational models, it has become the accepted wisdom that lifetime acclimation (e.g. via learning) smooths the fitness landscape and consequently accelerates evolution. However, analytical studies, focusing on the effect of phenotypic plasticity on evolution in simple unimodal landscapes, have often found that learning hinders the evolutionary process rather than accelerating it. Here, we provide a general framework for studying the effect of plasticity on evolution in multipeaked landscapes and introduce a rigorous mathematical analysis of these dynamics. We show that the convergence rate of the evolutionary process in a given arbitrary one-dimensional fitness landscape is dominated by the largest descent (drawdown) in the landscape and provide numerical evidence to support an analogous dominance also in multidimensional landscapes. We consider several schemes of phenotypic plasticity and examine their effect on the landscape drawdown, identifying the conditions under which phenotypic plasticity is advantageous. The lack of such a drawdown in unimodal landscapes vs. its dominance in multipeaked landscapes accounts for the seemingly contradictory findings of previous studies.

Phenotypic plasticity and evolution by genetic assimilation

In addition to considerable debate in the recent evolutionary literature about the limits of the Modern Synthesis of the 1930s and 1940s, there has also been theoretical and empirical interest in a variety of new and not so new concepts such as phenotypic plasticity, genetic assimilation and phenotypic accommodation. Here we consider examples of the arguments and counter-arguments that have shaped this discussion. We suggest that much of the controversy hinges on several misunderstandings, including unwarranted fears of a general attempt at overthrowing the Modern Synthesis paradigm, and some fundamental conceptual confusion about the proper roles of phenotypic plasticity and natural selection within evolutionary theory.

Psychological altruism vs. biological altruism: narrowing the gap with the Baldwin effect

This paper defends the position that the supposed gap between biological altruism and psychological altruism is not nearly as wide as some scholars (e.g., Elliott Sober) insist. Crucial to this defense is the use of James Mark Baldwin's concepts of "organic selection"and "social heredity" to assist in revealing that the gap between biological and psychological altruism is more of a small lacuna. Specifically, this paper argues that ontogenetic behavioral adjustments, which are crucial to individual survival and reproduction, are also crucial to species survival. In particular, it is argued that human psychological altruism is produced and maintained by various sorts of mimicry and self-reflection in the aid of both individual and species survival. The upshot of this analysis is that it is possible to offer an account of psychological altruism that is closely tethered to biological altruism without reducing entirely the former to the latter.

The evolution of the neocortex in mammals: how is phenotypic diversity generated?

Evolution of the mammalian neocortex is difficult to examine directly. For this reason, comparative studies and developmental studies are the best way of gaining insight into the evolutionary process. Comparative studies indicate that neocortical evolution is constrained, and that the types of systems-level modifications made to the neocortex are limited. Developmental studies of gene expression suggest that genetic contingencies set up aspects of cortical organization and connectivity, and that the complex spatial and temporal interactions of genes constrain development and evolution. Although genes obviously contribute to phenotypic variability, variability can also be achieved through alterations in the sensory receptor arrays, or changes in sensory driven activity. The intracellular mechanisms that enable phenotypic variability might evolve, but often the phenotypic characteristic in question is context-dependent.