While evolutionary computation is well suited for automatic discovery in engineering, it can also be used to gain insight into how humans and organizations could perform more effectively. Using a real-world problem of innovation search in organizations as the motivating example, this dissertation formalizes human creative problem solving as competitive multi-agent search. It differs from existing single-agent and team-search problems in that the agents interact through knowledge of other agents' searches and through the dynamic changes in the search landscape caused by these searches. The main hypothesis is that evolutionary computation can be used to discover effective strategies for competitive multi-agent search. This hypothesis is verified in experiments using an abstract domain based on the NK model, i.e. partially correlated and tunably rugged fitness landscapes, and a concrete domain in the form of a social innovation game. In both domains, different specialized strategies are evolved for each different competitive environment, and also strategies that generalize across environments. Strategies evolved in the abstract domain are more effective and more complex than hand-designed strategies and one based on traditional tree search. Using a novel spherical visualization of the fitness landscapes of the abstract domain, insight is gained about how successful strategies work, e.g. by tracking positive changes in the landscape. In the concrete game domain, human players were modeled using backpropagation, and used as opponents to create environments for evolution. Evolved strategies scored significantly higher than the human models by using a different proportion of actions, providing insights into how performance could be improved in social innovation domains. The work thus provides a possible framework for studying various human creative activities as competitive multi-agent search in the future. / text

This paper provides an evolutionary perspective on financial systems based on complex systems theory. This perspective is used to organize the discussion about the convergence and non-convergence of financial systems. In recent years the discussion about the relative merits and the efficiency of market- and bank-based financial systems is subject to considerable academic and policy debate throughout the world. Bank- and market-based systems are found to give rise to different economic and corporate dynamics. Based on a notion of financial systems as configuration of complementary elements, it is suggested that the convergence of financial systems is best conceptualized as path dependent process of institutional change. This is illustrated with special reference to the recent developments of convergence of financial systems in Europe. The implication of the evolutionary perspective on financial systems is that neither theories using a simple evolutionary argument of survival of the fittest nor theories related to a institutional ossification perspective can provide much guidance for analyzing the transformations of financial systems. A multilevel institutional analysis which takes the interdependencies between national and firm-level institutions explicitly into account is required. (author's abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"