Organizational dynamics in adaptive distributed search processes: effects on performance and the role of complexity

Abstract

In this paper, the effects of altering the organizational setting of distributed adaptive search processes in the course of search are investigated. We put particular emphasis on the complexity of interactions between partial search problems assigned to search agents. Employing an agent-based simulation based on the framework of NK landscapes we analyze different temporal change modes of the organizational set-up. The organizational properties under change include, for example, the coordination mechanisms among search agents. Results suggest that inducing organizational dynamics has the potential to increase the effectiveness of distributed adaptive search processes with respect to various performance measures like the final performance achieved at the end of the search, the chance to find the optimal solution of the search problem, or the average performance per period achieved during the search process. However, results also indicate that the mode of temporal change in conjunction with the complexity of the search problem considerably affects the order of magnitude of these beneficial effects. In particular, results suggest that organizational dynamics induces a shift towards more exploration, i.e., discovery of new areas in the fitness landscape, and less exploitation, i.e., stepwise improvement.

Distributed Search Systems with Self-Adaptive Organizational Setups

“…The idea of self-adaptive distributed search systems builds on prior studies which provide evidence that distributed search processes could remarkably benefit with respect to solution quality obtained from inducing organiza tional dynamics while searching for better solutionsmay it be in the organizational setup of collaborating robots or "swarms" of unmanned aerial vehicles or in the organizational design of a firm where managers search for higher levels of firm performance [8], [9], [10], [11]. Apparently, organi za tional change per se tends to enhance the performance of a search system by inducing a shift towards more exploration, i.e., discovery of new solutions, and less exploitation, i.e., stepwise improve ment.…”

Special issue on distributed computing and artificial intelligence

“…The first paper by Wall (2016) investigates the effects of altering the organizational dynamics/setting of distributed adaptive search (DAS) processes, with emphasis on the complexity of interactions between partial search problems assigned to search agents. DAS processes occur in a large variety of real-world systems in which networked agents collaboratively search for higher levels of performance, obtaining collective intelligence, for which one scientific challenge is to coordinate and allow distributed agents to deal with the cross-agent interactions.…”