- author = "Francois-Michel {De Rainville} and Felix-Antoine Fortin and Marc-Andre Gardner and Marc Parizeau and Christian Gagne",
- title = "{DEAP} - Enabling Nimbler Evolutions",
- journal = "SIGEVOlution newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation",
- year = "2012",
- volume = "6",
- number = "2",
- pages = "17--26",
- keywords = "genetic algorithms, genetic programming",
- ISSN = "1931-8499",
-
URL = "
http://www.sigevolution.org/issues/pdf/SIGEVOlution0602.pdf",
-
code_url = "
https://github.com/DEAP/notebooks",
-
DOI = "
doi:10.1145/2597453.2597455",
- size = "10 pages",
- abstract = "DEAP is a Distributed Evolutionary Algorithm (EA) framework written in Python and designed to help researchers developing custom evolutionary algorithms. Its design philosophy promotes explicit algorithms and transparent data structures, in contrast with most other evolutionary computation softwares that tend to encapsulate standardised algorithms using the black-box approach. This philosophy sets it apart as a rapid prototyping framework for testing of new ideas in EA research. An executable notebook version of this paper is available at https://github.com/DEAP/notebooks.",
-
notes = "18 Feb 2014
. Building blocks for testing ideas . Rapid prototyping . Fully transparent . Parallel ready . Exhaustively documented . Available at http://deap.gel.ulaval.ca
Distributed Island model. Genealogy tree
The presented examples covered only a small part of DEAP's capabilities that include evolution strategies (including CMA-ES), multi-objective optimisation (NSGA-II and SPEA-II), co-evolution, particle swarm optimisation PSO, as well as many benchmarks (continuous, binary, regression, and moving peaks), and examples (more than 40).
Departement de genie electrique et de genie informatique - Universite Laval - Quebec (Quebec), Canada",
