Adaptation, Learning, and Behavior

This chapter identifies adaptation as the last major complexity concept. Unlike complex systems in physics and chemistry, the economy is a complex adaptive system, meaning that its parts—the economic agents—change their characteristics and behavior over time. Because of this property, complex adaptive systems are more difficult to analyze than complex systems. To understand adaptation, it is necessary to discuss the behavior and learning of agents, i.e. to adopt a microeconomic perspective. Based on insights from computational theory, the chapter argues that maximization is possible only for simple economic problems, which are rare. Most economic problems that are interesting are NP-hard and therefore intractable. Complexity economics rejects the standard rational choice approach of neoclassical economics in favor of the theoretically and empirically more plausible bounded rationality approach. In this respect, complexity economics overlaps with some branches of behavioral economics. An agent-based model of collective problem-solving and social learning is presented to emphasize that behavior has not only an individual but also a social aspect. Moreover, the chapter briefly discusses the link between complexity economics and the recently emerged narrative economics, which highlights the importance of sense-making for economic agents.