HAL-CGP

Cartesian genetic programming (CGP) in pure Python.

hal-cgp is an extensible pure Python library implementing Cartesian genetic programming to represent, mutate and evaluate populations of individuals encoding symbolic expressions targeting applications with computationally expensive fitness evaluations. It supports the translation from a CGP genotype, a two-dimensional Cartesian graph, into the corresponding phenotype, a computational graph implementing a particular mathematical expression. These computational graphs can be exported as pure Python functions, NumPy-compatible functions (Walt et al., 2011), SymPy expressions (Meurer et al., 2017) or PyTorch modules (Paszke et al., 2019).

The library implements a mu + lambda evolution strategy (Beyer and Schwefel, 2002) to evolve a population of individuals to optimize an objective function.

Figure from Jordan, Schmidt, Senn & Petrovici, “Evolving to learn: discovering interpretable plasticity rules for spiking networks”, arxiv:2005.14149.

• Installation
• Basic usage
• Documentation
  • Populations and individuals
  • Nodes
  • Searching numerical values for parameters via local search
• Examples
• API reference
  • High-level API
  • CGP Population structure
  • Nodes
  • Evolutionary Algorithms
  • Local search
• References
• Citation

Cartesian genetic programming (CGP) in pure Python. <https://happy-algorithms-league.github.io/hal-cgp/>