Python library for bio-inspired computational intelligence
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Latest commit c16ffc3 Jun 3, 2017 @aarongarrett committed on GitHub Merge pull request #11 from richardjgowers/master
Simplified iteration over observers and variators

README.rst

inspyred -- A framework for creating bio-inspired computational intelligence algorithms in Python.

Documentation Status Updates

inspyred is a free, open source framework for creating biologically-inspired computational intelligence algorithms in Python, including evolutionary computation, swarm intelligence, and immunocomputing. Additionally, inspyred provides easy-to-use canonical versions of many bio-inspired algorithms for users who do not need much customization.

Example

The following example illustrates the basics of the inspyred package. In this example, candidate solutions are 10-bit binary strings whose decimal values should be maximized:

import random
import time
import inspyred

def generate_binary(random, args):
    bits = args.get('num_bits', 8)
    return [random.choice([0, 1]) for i in range(bits)]

@inspyred.ec.evaluators.evaluator
def evaluate_binary(candidate, args):
    return int("".join([str(c) for c in candidate]), 2)

rand = random.Random()
rand.seed(int(time.time()))
ga = inspyred.ec.GA(rand)
ga.observer = inspyred.ec.observers.stats_observer
ga.terminator = inspyred.ec.terminators.evaluation_termination
final_pop = ga.evolve(evaluator=evaluate_binary,
                      generator=generate_binary,
                      max_evaluations=1000,
                      num_elites=1,
                      pop_size=100,
                      num_bits=10)
final_pop.sort(reverse=True)
for ind in final_pop:
    print(str(ind))

Requirements

  • Requires at least Python 2.6+ or 3+.
  • Numpy and Pylab are required for several functions in ec.observers.
  • Pylab and Matplotlib are required for several functions in ec.analysis.
  • Parallel Python (pp) is required if ec.evaluators.parallel_evaluation_pp is used.

License

This package is distributed under the MIT License. This license can be found online at http://www.opensource.org/licenses/MIT.

Resources

Features

  • TODO

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.