- author = "Owen Derby and Kalyan Veeramachaneni and Una-May O'Reilly",
- title = "Cloud Driven Design of a Distributed Genetic Programming Platform",
- booktitle = "Applications of Evolutionary Computing, EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY, EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR, EvoRISK, EvoROBOT, EvoSTOC",
- year = "2013",
- month = "3-5 " # apr,
- editor = "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and Ivanoe {De Falco} and Ernesto Tarantino and Carlos Cotta and Robert Schaefer and Konrad Diwold and Kyrre Glette and Andrea Tettamanzi and Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and Aniko Ekart and Francisco {Fernandez de Vega} and Sara Silva and Evert Haasdijk and Gusz Eiben and Anabela Simoes and Philipp Rohlfshagen",
- series = "LNCS",
- volume = "7835",
- publisher = "Springer Verlag",
- address = "Vienna",
- publisher_address = "Berlin",
- pages = "509--518",
- organisation = "EvoStar",
- keywords = "genetic algorithms, genetic programming, cloud computing, machine learning, distributed evolutionary computation, FlexGP",
- isbn13 = "978-3-642-37191-2",
-
DOI = "
doi:10.1007/978-3-642-37192-9_51",
- size = "10 pages",
- abstract = "We describe how we design FlexGP, a distributed genetic programming (GP) system to efficiently run on the cloud. The system has a decentralised, fault-tolerant, cascading startup where nodes start to compute while more nodes are launched. It has a peer-to-peer neighbour discovery protocol which constructs a robust communication network across the nodes. Concurrent with neighbour discovery, each node launches a GP run differing in parametrisation and training data from its neighbors. This factoring of parameters across learners produces many diverse models for use in ensemble learning.",
-
notes = "
EvoApplications2013 held in conjunction with EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
