Metacognitive Processes for Uncertainty Handling: Connectionist Implementation of a Cognitive Model

Metacognition in Computation

Volume

Papers from the 2005 AAAI Spring Symposium

Contents

An empirically based cognitive model of real-world decision making was implemented in Shruti, a system capable of rapid, parallel relational reasoning. The system effectively simulates a two-tiered strategy associated with proficient decisions makers: Recognitional or reflexive activation of expectations and associated responses, accompanied by an optional, recursive process of critiquing and correcting, regulated by the stakes of the problem, the time available, and the remaining uncertainty. The model and implementation are inconsistent with the conventional claim that decision makers fall back on formal analytical methods when pattern recognition fails. Instead, they learn simple metacognitive strategies to leverage reflexive knowledge in novel situations. In addition, the model suggests that the development of executive attention functions (metacognitive strategies) may be necessary for, and integral to, the development of working memory, or dynamic access to long term memory, and that strategies developed for uncertainty handling may accelerate the reflexive learning of remotely connected concepts.