Complexity and the limits to learning

In this paper we look at the manner in which ideas coming from complexity science change our understanding of the cognitive powers of agents that is really necessary to explain the evolution of markets and of firms. The general ideas behind complex systems dynamics and evolution are presented and then two examples are treated in detail. The first in an evolutionary model of a market in which some new product is developed by competing firms and their “task” is to find a strategy in terms of quality and price that will be sustainable. This essentially requires agents/firms to discover mutually compatible strategies, and to create thereby sustainable market niches. The second example considers the internal structure of firms, in terms of their constituent working practices and skills. It demonstrates that it is precisely their ignorance of the consequences of adopting any particular practice that generates diversity in the emergent capabilities of firms, exploring the dimension of potential demand and therefore leading to a successful and sustainable business sector. The work supports the notion that the cognitive abilities that are involved are not about deduction and logic, as a traditional view of rationality might suggest, but are about the development and contraction of interpretive frameworks, which will be different for each player. The paper links these examples to a general recognition of the idea that complex, multi-agent systems evolve through successive “structural attractors”—multi-dimensional dynamical systems—with temporary structural stability. Because real systems contain both the structure and deviations from it, then there is a constant probing of structural stability and the possibility of qualitative change to a new structural attractor. This resembles the ideas in biological evolution related to “punctuated equilibria,” but it also links this to the idea of emergent and evolving networks of interaction, never of course near thermodynamic equilibrium.