Distributed scheduling using simple learning machines

A new approach to develop parallel and distributed algorithms of scheduling tasks in parallel computers is proposed. A game theoretical model with the use of genetic-algorithms based learning machines called classifier systems as players in a game, serves as a theoretical framework of the approach. Experimental study of such a system shows its self-organizing features and the ability of collective behaviour. Following this approach a parallel and distributed scheduler is described. A simple version of the proposed scheduler has been implemented. Results of the experimental study of the scheduler demonstrate its high performance.