Parallel and Distributed Computational Intelligence
This January has been published Parallel and Distributed Computational Intelligence a book by F. Fernandez de Vega and E. Cantú-Paz Editors in the book series of Studies in Computational Intelligence of Springer. It comes with some of the most recent advances in distributed Evolutionary Algorithms, EDAs or cellular automaton using novel platforms such as Volunteer Computing in Desktop Grids and P2P, Graphics Processing Units or GRIDs. Within this context, some examples of applications for realistic problems are provided, for instance the case of Bioinformatics Data Mining or Protein Structure Prediction.
We have participated with the book chapter «Evolvable Agents: A Framework for Peer-to-Peer Evolutionary Algorithms» which has the following abstract:
Distributed evolutionary computation programs often needs increasingly big amounts of computational power when tackling large instances of hard optimization problems, and Peer-to-Peer (P2P) systems could be an option for building the large virtual supercomputer in which they could be run. Even as distributed Evolutionary Algorithms (EA) do take advantage of parallel execution by simultaneously promoting diversity and reducing runtime, there are still many challenges on the parallelization of EAs in P2P systems. In this chapter we present a survey of the state of the art in P2P EAs and our solutions to the main P2P issues such as decentralization, massive scalability and fault tolerance.
For those that decide to buy the book, I really hope that you enjoy reading!!
GeNeura Team 