ABSTRACT
This paper discusses problems of right retrievals of memory, preferential orderings, and script selection/withdrawal in natural language processing (NLP). Atmosphere is introduced to solve these problems. It works as a contextual indicator which roughly grasps what is being talked about. An implementation mechanism for atmosphere is presented inspired by artificial neural network researches. It is characterized by microfeature representation, a chronological FIFO (First-In First-Out memory), and threshold-based selection. The mechanism constructs an intuition module and works for NLP while cooperating with a logic module which uses TMS to check the justifications of preferential decisions done by the intuition module.
