From the ‘punctuated equilibrium' of Eldrege and Gould, through Lewontin's ‘triple helix' and the various visions and revisions of the Extended Evolutionary Synthesis (EES) of Laland and others, both data and theory have demanded an opening-up of the 1950's Evolutionary Synthesis that so firmly wedded evolutionary theory to the mathematics of gene frequency analysis. It can, however, be argued that a single deep and comprehensive mathematical theory may simply not be possible for the almost infinite varieties of evolutionary process active at and across the full range of scales of biological, social, institutional, and cultural phenomena. Indeed, the case history of 'meme theory' should have raised a red flag that narrow gene-centered models of evolutionary process may indeed have serious limitations. What is attempted here is less grand, but still broader than a gene-centered analysis. Following the instruction of Maturana and Varela that all living systems are cognitive, in a certain sense, and that living as a process is a process of cognition, the asymptotic limit theorems of information and control theories that bound all cognition provide a basis for constructing an only modestly deep but wider-ranging series of probability models that might be converted into useful statistical tools for the analysis of observational and experimental data related to evolutionary process. The line of argument in this series of interrelated essays proves to be surprisingly direct.
Author(s): Rodrick Wallace
Series: SpringerBriefs in Evolutionary Biology
Publisher: Springer
Year: 2023
Language: English
Pages: 176
City: Cham
Preface
An Introduction to the Formalism
On the Difference Between Cognitive and Physical System Dynamics
Iterating an Approach
Waiting for Kepler: Inadequacy of the Ergodic Decomposition
References
Contents
About the Author
1 On the Major Transitions
1.1 Introduction
1.2 Symmetry and Symmetry-Breaking
1.3 Resources
1.4 Cognition in Nonergodic Systems
1.5 The Prebiotic `Big Bang'
1.6 Biological `Recombination Transparency'
1.7 A Simple Application
1.8 Specialization and Cooperation: Multiple Workspaces
1.9 Discussion
1.10 Mathematical Appendix
Groupoids
The Data Rate Theorem
References
2 On the Extended Evolutionary Synthesis
2.1 Introduction
2.2 First Notions
2.3 The Basic Theory
2.4 Examples
2.5 More Theory: Selection Pressure as Shadow Price
2.6 Extending the Models
2.7 Discussion
2.8 Mathematical Appendix
References
3 On Regulation
3.1 Introduction
3.2 Theory
A Correspondence Reduction
Expanding the Model
Moving on: An Iterated Free Energy
An Iterated Data Rate Theorem
3.3 Applications
Imposing Stability in Second Order: Aperiodic Stochastic Amplification
Imposing Other Forms of Stability
Regulating Inherent Instability
Some Implications of These Examples
3.4 Discussion
3.5 Mathematical Appendix
Imposing Higher Order Stability
Seeking Higher Order Stability
Extending the Model
References
4 Punctuated Regulation as an Evolutionary Mechanism
4.1 Introduction
4.2 Fisher Zeros Reconsidered
4.3 Extinction I: Simple Noise-Induced Transitions
4.4 Extinction II: More Complicated Noise-Induced Transitions
4.5 Extinction III: Environmental Shadow Price
4.6 Discussion
4.7 Mathematical Appendix
References
5 Institutional Dynamics Under Selection Pressure and Uncertainty
5.1 Introduction
5.2 A Rate Distortion Theorem Model of Control
5.3 Selection Pressure Dynamics
A First Model
A Second Model
A Third Model
5.4 Destabilization By Delay
5.5 Extending the Data Rate Theorem
5.6 Moving On
5.7 Reconsidering Cognition An Sich
5.8 Changing the Viewpoint
5.9 Discussion
References
6 On `Speciation': Fragment Size in Information System Phase Transitions
6.1 Introduction
6.2 `Simple' Phase Transition
6.3 Phase Transitions in Networks of Information-Exchange Modules
6.4 Discussion
6.5 Mathematical Appendix: `Biological' Renormalizations
References
7 Adapting Cognition Models to Biomolecular Condensate Dynamics
7.1 Introduction
7.2 Resources
7.3 Cognition
7.4 Phase Transitions I: Fisher Zeros
7.5 Cognitive `Reaction Rate'
7.6 Phase Transitions II: Signal Transduction and Noise
7.7 Discussion
7.8 Mathematical Appendix: Groupoids
References
8 Evolutionary Exaptation: Shared Interbrain Activity in Social Communication
8.1 Introduction
8.2 Correlation
8.3 Cognition
Information and Other Resources
Cognition and Information
8.4 Dynamics
8.5 Cognition Rate
8.6 An Example
8.7 Cooperation: Multiple Workspaces
8.8 Network Topology Is Important
8.9 Time and Resource Constraints Are Important
8.10 Further Theoretical Development
8.11 Discussion
8.12 Mathematical Appendix
Groupoids
The Data Rate Theorem
Stochastic Analysis for Fig.8.5
Higher Dimensional Systems
References
9 Afterward
References
