A quantum model of exaptation: Incorporating potentiality into evolutionary theory

Abstract

The phenomenon of preadaptation, or exaptation (wherein a trait that originally evolved to solve one problem is co-opted to solve a new problem) presents a formidable challenge to efforts to describe biological phenomena using a classical (Kolmogorovian) mathematical framework. We develop a quantum framework for exaptation with examples from both biological and cultural evolution. The state of a trait is written as a linear superposition of a set of basis states, or possible forms the trait could evolve into, in a complex Hilbert space. These basis states are represented by mutually orthogonal unit vectors, each weighted by an amplitude term. The choice of possible forms (basis states) depends on the adaptive function of interest (e.g., ability to metabolize lactose or thermoregulate), which plays the role of the observable. Observables are represented by self-adjoint operators on the Hilbert space. The possible forms (basis states) corresponding to this adaptive function (observable) are called eigenstates. The framework incorporates key features of exaptation: potentiality, contextuality, nonseparability, and emergence of new features. However, since it requires that one enumerate all possible contexts, its predictive value is limited, consistent with the assertion that there exists no biological equivalent to "laws of motion" by which we can predict the evolution of the biosphere.

Toward a Quantum Theory of Humor

“…The concept of potentiality has broad implications across the sciences; for example, every biological trait not only has direct implications for existing phenotypic properties such as fitness, but both enables and constrains potential future evolutionary changes for a given species. The quantum approach been used to model the biological phenomenon of exaptation-wherein a trait that originally evolved for one purpose is co-opted for another (possibly after some modification) [40]. The term exaptation was coined by Gould and Vrba [41] to denote what Darwin referred to as preadaptation 1 .…”

“…Like other kinds of evolutionary change, exaptation is observed across all levels of biological organization, i.e., at the level of genes, tissue, organs, limbs, and behavior. Quantum models have also been used to model the cultural analog of exaptation, wherein an idea that was originally developed to solve one problem is applied to a different problem [40]. For example, consider the invention of the tire swing.…”

La evolución de los sistemas complejos adaptativos según el “darwinismo cuántico” de Zurek

“…Las leyes físicas definen el ámbito de lo posible y la contingencia histórica, sin violarlas, explica el mundo de las formas actualizadas (manifiestas en el mundo real) que sin embargo no es sino una ínfima fracción dentro de los muchos mundos posibles. Sotolongo y Delgado (2006), Ulanowicz (2009a), Gabora et al (2013) independientemente justifican la prevalencia de la semiosis sobre la causalidad física cuando la combinatoria de posibilidades futuras realmente accesibles sobrepasa la capacidad de las leyes universales para determinar los resultados. En este sentido la explicación física (termodinámica y cuántica) no entra en conflicto radical con la explicación histórica y contingente adoptada previamente por el darwinismo.…”

Toward an evolutionary-predictive foundation for creativity

“…An alternative is to model the evolution of creative ideas as a Lamarckian process, drawing on formal models of concept combination (which lends itself to mathematical modeling more readily than some other creative processes) (e.g., Aerts & Gabora, 2005;Gabora, 2013;Gabora & Aerts 2009). The approach addresses the challenge of modeling the emergence of new attributes (such as emergence of the concept of a spout during the invention of a teapot) (Gabora, & Carbert, 2015;Gabora, Scott, & Kauffman, 2013). Emergent features are common in creative concept combination (e.g., Estes & Ward, 2002), but to our knowledge they are not currently addressed by the prediction literature nor by any mathematical model of creativity that treats it as variation and selection amongst thought trials (e.g., Simonton, 2013Simonton, , 2014.…”