The Cognitive Cycle
John F. Sowa · Annals of Computer Science and Information Systems · 2015
In the twenty years from first grade to a PhD, students never learn any subject by the methods for which machine-learning algorithms have been designed.Those algorithms are useful for analyzing large volumes of data.But they don't enable a computer system to learn a language as quickly and accurately as a three-year-old child.They're not even as effective as a mother raccoon teaching her babies how to find the best garbage cans.For all animals, learning is integrated with the cognitive cycle from perception to purposeful action.Many algorithms are needed to support that cycle.But an intelligent system must be more than a collection of algorithms.It must integrate them in a cognitive cycle of perception, learning, reasoning, and action.That cycle is key to designing intelligent systems. I. THEORIES OF LEARNING AND REASONINGHE nature of the knowledge stored in our heads has major implications for educating children and for designing intelligent systems.Both fields organize knowledge in teachable modules that are presented in textbooks and stored in well structured databases and knowledge bases.A systematic organization makes knowledge easier to teach and to implement in computer systems.But as every student discovers upon entering the workforce, "book learning" is limited by the inevitable complexities, exceptions, and ambiguities of engineering, business, politics, and life.Although precise definitions and specifications are essential for solving problems in mathematics, science, and engineering, most problems aren't well defined.As Shakespeare observed, "There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy." The Cognitive Cycle