The design of adaptive systems: optimal parameters for variation and selection in learning and development

Area of Science:

• Evolutionary biology
• Developmental biology
• Cognitive science

Background:

• Learning and development can involve evolutionary processes within an organism.
• Trial-and-error learning generates variants, with selection rules filtering them.
• Cellular lineage selection can drive development.

Purpose of the Study:

• Analyze abstract properties of internal selective systems.
• Understand evolutionary dynamics within organisms.
• Apply concepts from evolutionary genetics to learning and development.

Main Methods:

• Applied the Price Equation and Fisher's fundamental theorem of natural selection.
• Analyzed generative mechanisms and selective filters as genetically controlled phenotypes.
• Examined internal selective systems in learning and development.

Main Results:

• Internal selective systems balance performance improvement with deterioration.
• Selective improvement rate equals fitness variance.
• Generative mechanisms create variation; selective filters optimize performance.

Conclusions:

• The Price and Fisher methods offer a general framework for internal selection.
• This framework provides insights into adaptive systems across genetics, learning, and development.
• Applied to honey bee foraging, clarifying gene-phenotype relations in internal selection.