Abstract :
Intelligence is a driving force or an ability to acquire and use knowledge and skills, or to inference in problem solving. This keynote lecture describes the taxonomy and nature of intelligence. It analyzes roles of information in the evolution of human intelligence, and the needs for logical abstraction in modeling the brain and natural intelligence. A formal model of intelligence is developed known as the generic intelligence mode (GIM), which provides a foundation to explain the mechanisms of advanced natural intelligence such as thinking, learning, and inferences. A measurement framework of intelligent capability of humans and systems is presented in the forms of intelligent quotient, intelligent equivalence, and intelligent metrics. On the basis of GIM model and theories, the compatibility of nature and machine intelligence is revealed, which forms a theoretical foundation for rigorous study in machine intelligence, AI, and intelligent systems.
Keywords :
inference mechanisms; problem solving; cognitive informatics foundations; generic intelligence mode; human intelligence; inference; intelligent equivalence; intelligent metrics; intelligent quotient; machine intelligence; problem solving; Artificial intelligence; Brain modeling; Cognitive informatics; Humans; Information analysis; Intelligent systems; Learning systems; Machine intelligence; Problem-solving; Taxonomy; AI; Cognitive informatics; GIM; LRMB; OAR; RTPA; brain science; cognitive models; cognitive processes; concept algebra; denotational mathematics; intelligence science; intelligent measurement; intelligent metrics; intelligent quotient; mathematical models;
