Pei Wang - A General Theory of Intelligence [an e-book under development] | Home
This eBook is an attempt to establish a theory that identifies the commonality within various forms intelligence, including human intelligence, computer intelligence, animal intelligence, alien intelligence, group intelligence, etc. -- NARS (Non-Axiomatic Reasoning System) - Most of the existing AI inference works with semi-axiomatic systems, which attempt to make partial extension or revision of mathematical logic, while keeping the other parts. What AI really needs are non-axiomatic systems, which do not assume the sufficiency of knowledge and resources in any aspect of the system. NARS is a concrete example of non-axiomatic system which uses a formal language "Narsese" to represent goals, actions, and beliefs.The basic unit of the language is term, which can be thought of as the name or label of a concept in the system. (..) The meaning of a term is determined by its extension and intension, which are the collection of the inheritance relations between this term and other terms, obtained from the experience of the system. NARS includes three variants of the inheritance relation: similarity (symmetric inheritance), implication (derivability), and equivalence (symmetric implication). (..)The meaning of a compound term is partially determined by its logical relations with its components, and partially by the system's experience on the compound term as a whole. Event is a special type of statement that have a time-dependent truth-value. Operation is a special type of event that can occur by the system's decision. Goal is a special type of event, that the system is attempting to realize, by carrying out certain operations. Beside goals to be achieved, NARS can accept tasks that are knowledge to be absorbed and questions to be answered. (..)If a event is judged to imply the achieving of a goal, then the desirability of the event is increased, and the system will also evaluate its plausibility(..). When an event is both desirable and plausible, the system will make the decision to turn the event into a goal to be actually pursued. The basic function of inference rules in NARS is to derive new beliefs from current beliefs.
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