A parallel distributed processing model of story comprehension and recall

An optimal control theory of story comprehension and recall is proposed within the framework of a “situation”‐state space. A point in situation‐state space is specified by a collection of propositions, each of which can have the values of either “present” or “absent.” A trajectory in situation‐state space is a temporally ordered sequence of situations. A reader's knowledge that the occurrence of one situation is likely to cause the occurrence of another situation is represented by a subjective conditional probability distribution. A multistate probabilistic (MSP) causal chain notation is also introduced for conveniently describing the knowledge structures implicitly represented by the subjective conditional probability distribution. A story is represented as a partially specified trajectory in situation‐state space, and thus, story comprehension is defined as the problem of inferring the most probable missing features of the partially specified story trajectory. The story‐recall process is also viewed as ...

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