- author = "Mark Harman and Yue Jia and William B. Langdon and Justyna Petke and Iman Hemati Moghadam and Shin Yoo and Fan Wu",
- title = "Genetic Improvement for Adaptive Software Engineering",
- booktitle = "9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'14)",
- year = "2014",
- editor = "Gregor Engels",
- pages = "1--4",
- address = "Hyderabad, India",
- month = "2-3 " # jun,
- publisher = "ACM",
- note = "Keynote",
- keywords = "genetic algorithms, genetic programming, SBSE, Artificial Intelligence, Machine Learning, Genetic Improvement, Search Based Software Engineering",
- isbn13 = "978-1-4503-2864-7",
-
URL = "
http://www.cs.ucl.ac.uk/staff/mharman/seams14.pdf",
-
URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/gismo/seams14main-id100-p-22852-aede8e5-20619-submitted.pdf",
-
DOI = "
doi:10.1145/2593929.2600116",
- acmid = "2600116",
- size = "4 pages",
- abstract = "This paper presents a brief outline of an approach to online genetic improvement. We argue that existing progress in genetic improvement can be exploited to support adaptivity. We illustrate our proposed approach with a dreaming smart device example that combines online and offline machine learning and optimisation.",
-
notes = "
http://seams2014.uni-paderborn.de/ Co-located with ICSE 2014
978-1-4503-2864-7/14/06",
