Innovations are new idea, device or process. Innovations are the application of better solutions that meet new requirements, inarticulated needs or existing market needs. It is proficient through more effective products, processes, services, technologies, or new ideas that are readily available to markets, governments and society. Innovations are something original and novel, as a significant, new that breaks into the market or society. Spurred by the growth of the World Wide Web and the Internet, and their similarity to numerous other large, dynamic, real-life networks, a truly cross-disciplinary science of complex networks has emerged in the past 15 years. Hundreds of studies have been conducted and papers published exploring properties of complex such as, their size, diameter, degree distribution, pairwise-distance distribution, cliques, communities, clustering coefficient, and the like. Several growth models of these evolving networks have been proposed and studied. However, an area of active interest, which has not been studied adequately, is that of designing control policies to steer the evolution of such a network towards a desired goal. In practical situations, such as controlling the spread of diseases or the formation of opinions, topological properties, of the network, may need to be controlled. It would, therefore, be valuable to have automated synthesis of strategies for controlling relevant topological properties of complex networks described by, for example, a preferential-attachment and preferential-deletion model. We propose that an automated optimal control of evolving complex networks be achieved by leveraging recent results in developing stochastic models for the evolution of complex networks in combination with the classical results on dynamic-programming algorithms for optimal control.
Last date updated on June, 2014