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Science has made great strides in modeling space, time, mass and energy. Yet little attention has been paid to the precise representation of the information ubiquitous in nature.
Introduction to Evolutionary Informatics fuses results from complexity modeling and information theory that allow both meaning and design difficulty in nature to be measured in bits. Built on the foundation of a series of peer-reviewed papers published by the authors, the book is written at a level easily understandable to readers with knowledge of rudimentary high school math. Those seeking a quick first read or those not interested in mathematical detail can skip marked sections in the monograph and still experience the impact of this new and exciting model of nature's information.
This book is written for enthusiasts in science, engineering and mathematics interested in understanding the essential role of information in closely examined evolution theory.
The Queen of Scientists & Engineers
Science and Models
Information. What is It?:
Design Search in Evolution and the Requirement of Intelligence:
Design as Search
Design by Computer
Designing a Good Pancake
Sources of Knowledge
The Curse of Dimensionality & the Need For Knowledge
A Smörgåsbord of Search Algorithms
Determinism in Randomness:
Bernoulli's Principle of Insufficient Reason
The Need for Noise
Conservation of Information in Computer Search:
What is Conservation of Information?
The Astonishing Cost of Blind Search in Bits
Measuring Search Difficulty in Bits
Sources of Information in Evolutionary Search
Stairstep Information & Transitional Functional Viability
The Search for the Search
Analysis of Some Biologically Motivated Evolutionary Models:
EV: A Software Model of Evolution
Avida: Stair Steps to Complexity Using NAND Logic
Conclusion: Sweeping a Dirt Floor
Measuring Meaning: Algorithmic Specified Complexity:
The Meaning of Meaning
Conditional KCS Complexity
Defining Algorithmic Specified Complexity (ASC)
Examples of ASC
Meaning is in the Eye of the Beholder
Intelligent Design & Artificial Intelligence:
Turing & Lovelace: One is Strong and the Other One's Dead
ID & the Unknowable
Readership: General / Popular; Enthusiasts in science, engineering and apologetics and to those interested in the information theoretic components of closely examined evolution.