Simulated evolution and learning [electronic resource] : 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014 : proceedings / Grant Dick [and 11 others] (Eds.).
2014
QA76.618 .S43 2014eb
Linked e-resources
Linked Resource
Details
Title
Simulated evolution and learning [electronic resource] : 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014 : proceedings / Grant Dick [and 11 others] (Eds.).
ISBN
9783319135632 electronic book
3319135635 electronic book
9783319135625
3319135627
3319135635 electronic book
9783319135625
3319135627
Published
Cham : Springer, [2014]
Copyright
©2014
Language
English
Description
1 online resource (xvi, 862 pages) : illustrations.
Call Number
QA76.618 .S43 2014eb
Dewey Decimal Classification
006.3/823
Summary
This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.
Note
Includes author index.
Access Note
Access limited to authorized users.
Added Author
Series
Lecture notes in computer science ; 8886.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
Linked Resources
Record Appears in
Table of Contents
Evolutionary optimization
Evolutionary multi-objective optimization
Evolutionary machine learning
Theoretical developments
Evolutionary feature reduction
Evolutionary scheduling and combinatorial optimization
Real world applications and evolutionary image analysis.
Evolutionary multi-objective optimization
Evolutionary machine learning
Theoretical developments
Evolutionary feature reduction
Evolutionary scheduling and combinatorial optimization
Real world applications and evolutionary image analysis.