Problem Solving by Heterogeneous Agents

A substantial amount of economic activity involves problem solving, yet economics has few, if any, formal models to address how agents of limited abilities find good solutions to difficult problems. In this paper, we construct a model of heterogeneous agents of bounded abilities confronting difficult problems and analyze their individual and collective performance. By heterogeneity, we mean differences in how individuals represent problems internally, their perspectives, and in the algorithms they use to generate solutions, their heuristics. With this model, we find that a collection of bounded but diverse agents can locate optimal solutions to very difficult problems. We can also calculate the marginal benefits to adding additional problem solvers. We find that problem solving firms can exhibit arbitrary returns to scale, that the order that problem solvers are applied to a problem can matter, and that the standard story of decreasing returns to scale is unlikely.