Natural selection maximizes Fisher information
arXiv:0901.3742 · doi:10.1111/j.1420-9101.2008.01647.x
Abstract
In biology, information flows from the environment to the genome by the process of natural selection. But it has not been clear precisely what sort of information metric properly describes natural selection. Here, I show that Fisher information arises as the intrinsic metric of natural selection and evolutionary dynamics. Maximizing the amount of Fisher information about the environment captured by the population leads to Fisher's fundamental theorem of natural selection, the most profound statement about how natural selection influences evolutionary dynamics. I also show a relation between Fisher information and Shannon information (entropy) that may help to unify the correspondence between information and dynamics. Finally, I discuss possible connections between the fundamental role of Fisher information in statistics, biology, and other fields of science.
Published version freely available at DOI listed here
Cited by in corpus (22)
- Natural selection. IV. The Price equation
- The contribution of statistical physics to evolutionary biology
- Escort Evolutionary Game Theory
- The Price equation program: simple invariances unify population dynamics, thermodynamics, probability, information and inference
- Principle of Maximum Fisher Information from Hardy's Axioms Applied to Statistical Systems
- Universal expressions of population change by the Price equation: natural selection, information, and maximum entropy production
- The free energy requirements of biological organisms; implications for evolution
- Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory
- d'Alembert's direct and inertial forces acting on populations: the Price equation and the fundamental theorem of natural selection
- Simple unity among the fundamental equations of science
- On the accessibility of adaptive phenotypes of a bacterial metabolic network
- Universal constraint on nonlinear population dynamics
- The fundamental equations of change in statistical ensembles and biological populations
- How Turing parasites expand the computational landscape of digital life
- Automatic differentiation and the optimization of differential equation models in biology
- Non-parametric estimation of Fisher information from real data
- Measurement of statistical evidence on an absolute scale following thermodynamic principles
- Stochastic thermodynamics of Fisher information
- A Theory of Intelligences
- Classical Geometric Fluctuation Relations
- The Price equation reveals a universal force-metric-bias law of algorithmic learning and natural selection
- Information and (co-)variances in discrete evolutionary genetics involving solely selection