Skip to Main Content
Psychological theories of problem solving have largely focused on explicit processes that gradually bring the solver closer to the solution step-by-step in a mostly explicit and deliberative way. This approach to problem solving is typically inefficient or ineffective when the problem is too complex, ill-understood, or ambiguous. In such a case, a `creative' approach to problem solving might be more appropriate. We propose a computational psychological model implementing the Explicit-Implicit Interaction theory of creative problem solving (i.e., the CLARION theory of creative problem solving) that centers on the interaction of implicit and explicit processing. The model based on the CLARION theory has been used to simulate a variety of empirical psychological data sets.