Evolution

As explained in Grokking AI Algorithms, Second Edition

Evolution is the cumulative change in inherited characteristics of populations across generations through variation and differential survival or reproduction.

Evolution is the gradual accumulation of inherited changes in populations across generations. Offspring vary because they inherit mixed traits and small mutations; variants that fit their environment tend to survive and reproduce more. section 4.1

Evolution is not a straight ladder from primitive to modern forms. It branches into a changing cloud of variants: many disappear, while some thrive as environments favor their traits. section 4.1

Peppered moths

Light-colored moths were once common because they blended into light surfaces, while dark moths made up about 2% of the population. After the Industrial Revolution, dark moths reached about 95%, illustrating adaptation through differential survival. section 4.1

Figure 4.1 The idea of linear human evolution vs. actual human evolution

Compare the familiar linear picture of evolution with its branching reality. section 4.1

How Grokking AI Algorithms, Second Edition covers it

How deep it goes

Explains variation, mutation, branching populations, and selection through intuition and examples, stopping short of detailed biology.

Examples

Uses branching human evolution, peppered moth coloration, and reproduction with mutation to illustrate evolutionary change.

What you can do after

Evaluate/understand how populations change through inherited variation and environmental selection.

How it connects

Connects evolution with natural selection, mutation, adaptation, survival, reproduction, and evolutionary algorithms.

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Also explained in

• 

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  Evolutionary Deep Learning: Genetic algorithms and neural networksBiological evolution is the change in heritable characteristics of populations across generations through processes such as variation and selection.
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  Architecture Modernization: Socio-technical alignment of software, strategy, and structureEvolution is the progression of a component from novel and uncertain origins toward increasingly industrialized, stable, and efficient forms.

Compare how 3 books explain evolution →

Related concepts

• evolutionary computationused by · Evolutionary computation is a family of search and optimization methods that iteratively improve candidate solutions through variation and selection inspired by biological evolution.
• natural selectionproduced by · Natural selection is the evolutionary process by which heritable traits affecting survival or reproduction influence which variants become more common in a population.
• Wardley Mappingused by · Wardley Mapping is a visual strategy technique that maps user needs and supporting components in a value chain and positions them by evolutionary maturity.
• acceleratorproduced by · An accelerator is an action intended to speed the evolution of one or more components in a strategic landscape.
• model architectureused by · The structural organization of a computational system’s components, relationships, and operations that determines how it processes information or behaves.

This explainer was generated by Manning's knowledge graph from the text of Grokking AI Algorithms, Second Edition. The section links point to the parts of the book it draws on.