Abstract
An experience-grounded semantics is introduced for an intelligent reasoning system, which is adaptive, and works with insufficient knowledge and resources. According to this semantics, truth and meaning are defined with respect to the experience of the system – the truth value of a statement indicates the amount of available evidence, and the meaning of a term indicates its experienced relations with other terms. The major difference between experience-grounded semantics and model-theoretic semantics is that the former does not assume the sufficiency of knowledge and resources. This approach provides new ideas to the solution of some important problems in cognitive science.
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