期刊信息
Genetic Programming and Evolvable Machines
https://link.springer.com/journal/10710
影响因子:
1.700
出版商:
Springer
ISSN:
1389-2576
浏览:
9540
关注:
2
征稿
Aims and scope

The journal of Genetic Programming and Evolvable Machines is devoted to reporting innovative and significant progress in automatic evolution of software and hardware. Methods for artificial evolution of active components, such as programs or machines, are rapidly developing branches of adaptive computation and adaptive engineering. They entail the development, evaluation and application of methods that mirror the process of neo-Darwinian evolution and produce as a result computational expressions such as algorithms or machines such as mechanical or electronic devices that actively process environmental information and transform their environment. In addition to its main topics, the journal covers related topics such as evolutionary algorithms with variable-size genomes, alternate methods of program induction, approaches to engineering systems development based on embryology, morphogenesis or other techniques inspired by adaptive natural systems.

Methods:

Genetic Programming; Variable-size evolutionary algorithms; Induction of algorithms and symbolic expressions by iterative and non-deterministic search; Evolutionary design and Optimization of electronic circuits and mechanical devices; On-line adaptation of hardware and software; Evolutionary robotics; DNA computing; Coevolutionary techniques; Meta-learning; Hybrid systems; Cellular and Developmental approaches.

Task Domains:

Algorithm evolution; Agents; Architecture; Art and animation; Classification and pattern recognition; Computer graphics; Computing; Circuit design; Data mining; Distributed problem solving; Engineering design applications; Games; Hardware and software testing and verification; Image and signal processing; Interactive evolution; Molecular biology applications; Music; Natural language processing; Network routing; Optimization; Process control; Robotics and motor control; Self-repair; Self-reproduction of software and hardware, Self-programming; System modeling.

Both theoretical papers (preferably including computer simulations) and application papers are welcome. Papers describing hardware implementations are strongly encouraged. Papers in the areas of artificial life, molecular computing and any other emergent computation technique will be considered as well.
最后更新 Dou Sun 在 2024-07-21
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