Abstract: Mobile wireless devices such a telephones, PDAs and webpads are getting more powerful and have low duty cycles. To exploit this untapped resource, a method is described which allows computing tasks to be (optionally parallelized and) distributed among large numbers of such wireless devices and the cost of such services apportioned accordingly.

Abstract: A computer system comprises at least one genetic optimization agent holding a pool of genotypes, representing possible solutions to a problem. The genetic optimization agent generates new genotypes from the pool, evaluates the new genotypes according to predetermined fitness criteria, and selects the fittest of the genotypes to form a new generation of genotypes in the pool. The system also includes a number of further agents, for generating further solutions to the problem, using different techniques, such as simulated annealing, constraint logic, and neural networks. These further solutions are also represented by genotypes. The genetic optimization agent imports genotypes from the further agents and adds them to its pool of genotypes for breeding and selection. The genetic optimization agent thus provides a way of integrating a number of different problem-solving agents, in such a way as to achieve synergy between them.