Abstract

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 the key to designing intelligent systems.

Short Bio

John F. Sowa spent 30 years working on R & D projects at IBM and is a cofounder of VivoMind Research, LLC. He has a BS in mathematics from MIT, an MA in applied mathematics from Harvard, and a PhD in computer science from the Vrije Universiteit Brussel. He is a fellow of the American Association for Artificial Intelligence, and he has published several books and many articles on artificial intelligence, computational linguistics, and related areas of cognitive science. With his colleagues at VivoMind, he has been developing novel methods of learning, reasoning, and language understanding. The system of conceptual graphs, which he designed, has been adopted as one of the principal dialects of the ISO/IEC standard 24707 for Common Logic.