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.
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))
- Requires Python 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_ppis used.
This package is distributed under the MIT License. This license can be found online at http://www.opensource.org/licenses/MIT.
- Homepage: http://aarongarrett.github.io/inspyred
- Email: garrett@inspiredintelligence.io
- Documentation: https://inspyred.readthedocs.io.
Garrett, A. (2012). inspyred (Version 1.0.1) [software]. Inspired Intelligence. Retrieved from https://github.com/aarongarrett/inspyred [accessed CURRENT DATE].
- TODO
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.