MIDCA: A Metacognitive, Integrated Dual-Cycle Architecture for Self-Regulated Autonomy

The results of autonomy are often some mechanism Research on cognitive architectures have made significant by which we automate system behavior and decision-making contributions over the years including the ability to reason computationally. We claim that for a system to exhibit with multiple knowledge modes (Laird 2012), to introspectively self-regulated autonomy, however, it must have a model of examine the rationale for a decision (Forbus, Klenk itself in addition to the usual model of the world. Like selfregulated and Hinrichs 2009), and the ability to learn knowledge of learning (e.g., Bjork, Dunlosky and Kornell 2013), varied levels of abstraction (Langley and Choi 2006). Comparatively whereby a learner manages the pace, resources, and goals of less research efforts examine the metacognitive learning, self-regulated autonomy involves a system that contributions to effective decision-making and behavior.