Design of Metacontrol and Metacognition mechanisms in SMCA Using Norms and Affect rules

This research paper investigation concerned with understanding the mechanisms and designing a rules of Metacontrol and Metacognition. This work investigated the concept of metacognition as a powerful catalyst for control, unify and self-reflection. Metacontrol is a part of the Metacognition task. Metacontrol rules decides which deliberative agents are to be learned and ready to perform in different conditions. The deliberative actions are called control action. A Metacontroller determines the relevant control actions. Metacognition is used on BDI models with respect to planning, reasoning, decision making, self reflection, problem solving, learning and the general process of cognition to improve performance. One perspective on how to develop metacognition in a cognitive model is based on the differentiation between metacognitive strategies and metacomponents or metacognitive aids. Metacognitive strategies denote activities such as Metacomphrension (remedial action). Metacognition agents follow well aligned norms, perceptual range, metarules, learning and affect values to maximize its own reward.