A framework for creating bio-inspired computational intelligence algorithms in Python
Project description
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
Homepage: http://aarongarrett.github.io/inspyred
Email: aaron.lee.garrett@gmail.com
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