- author = "Juan Luis Jim\'enez Laredo and Daniel {Lombra\~na Gonz\'alez} and Francisco {Fern\'andez de Vega} and Maribel Garc\'ia Arenas and Juan Juli\'an {Merelo Guerv\'os}",
- title = "A Peer-to-Peer Approach to Genetic Programming",
- booktitle = "Proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011",
- year = "2011",
- month = "27-29 " # apr,
- editor = "Sara Silva and James A. Foster and Miguel Nicolau and Mario Giacobini and Penousal Machado",
- series = "LNCS",
- volume = "6621",
- publisher = "Springer Verlag",
- address = "Turin, Italy",
- pages = "108--117",
- organisation = "EvoStar",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-642-20406-7",
-
DOI = "
doi:10.1007/978-3-642-20407-4_10",
- abstract = "This paper proposes a fine-grained parallelization of the Genetic Programming paradigm (GP) using the Evolvable Agent model evagbp The algorithm is decentralised in order to take full-advantage of a massively parallel Peer-to-Peer infrastructure. In this context, GP is particularly demanding due to its high requirements of computational power. To assess the viability of the approach, the evag model has been empirically analysed in a simulated Peer-to-Peer environment where experiments were conducted on two well-known GP problems. Results show that the spatially structured nature of the algorithm is able to yield a good quality in the solutions. Additionally, parallelisation improves times to solution by several orders of magnitude.",
-
notes = "See also \cite{Laredo:thesis}.
Newscast P2P protocol from EU DREAM project. Agents are lightweight computing threads. Possibly many threads per node. Emigration within distributed GP population integrated with stochastic establishment of directly links in P2P application layer protocol.
Part of \cite{Silva:2011:GP} EuroGP'2011 held in conjunction with EvoCOP2011 EvoBIO2011 and EvoApplications2011",
