Problem solving: Understanding complexity as uncertainty

Abstract

Understanding complexity has dominated the domain of problem solving. There needs to be a cohesive idea about what makes problem solving hard in contexts broadly described as complex, and what are the sources of errors in problem solving in situations thought to be complex. This chapter argues that our understanding of complexity requires an overhaul, and perhaps a more encouraging and fruitful way forward in research on complex problem solving, is to reconceptualise “finding solutions to complex problems” as instead “findings ways of reducing uncertainty”. This entails redefining the domain of “complex dynamic problem solving” into “decision making under uncertainty”. This enables a Bayesian approach to understanding what makes a situation controllable, or appear to be controllable to a problem solver, and hence what cognitive and psychological factors they bring to bear on the situation.