DEAP-ER documentation

DEAP-ER is a typed evolutionary-algorithm toolbox for Python 3.12 and newer. Register operators, run an algorithm. The published surface covers genetic algorithms and mixed encodings, tree and columnar GP (including memetic and semantic search helpers and a private Push policy loop), CMA (boxed, separable, restarting, and MO-CMA), multi-objective and quality-diversity search, case-structured selection, co-evolution and island stepping, parallel evaluation, records and checkpoints, and common benchmarks.

The library started as a rewrite of DEAP. The toolbox model is the same; it is not a drop-in rename.

• Introduction
• Differences with DEAP
• Performance
• Getting started
• Roadmap
• Tutorials
• Examples
• API reference