An account of cognitive flexibility and inflexibility for a complex dynamic task

Problem solving involves adapting known problem solving methods and strategies to the task at hand (Schunn & Reder, 2001) and cognitive flexibility is considered to be “the human ability to adapt the cognitive processing strategies to face new and unexpected conditions of the environment” (Cañas et al., 2005, p. 95). This work presents an ACT-R 6.0 model of complex problem solving behavior for the dynamic microworld game FireChief (Omodei & Wearing, 1995) that models the performance of participants predisposed to behave either more or less flexibly based on the nature of previous training on the task (Cañas et al., 2005). The model exhibits a greater or lesser degree of cognitive inflexibility in problem solving strategy choice reflecting variations in task training. The model provides an explanation of dynamic task performance compatible with the Competing Strategies paradigm (Taatgen et al., 2006) by creating a second layer of strategy competition that renders it more flexible with respect to strategy learning, and provides an explanation of cognitive inflexibility based on reward mechanisms.