Proceedings of the Annual Meeting of the Cognitive Science Society

An optimal control theory of story comprehension and recall is proposed within the framework of a "situation" stale 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". Story comprehension is viewed as finding a temporally-ordered sequence of situations or "trajectory" which is consistent with story-imposed constraints. Story recall is viewed as finding a trajectory consistent with episodic memory constraints. A multistate probabilistic (MSP) machine representational scheme is then introduced for compactly and formally assigning a "degree of belief (i.e., a probability value) to each trajectory in the slate space. A connectionist model is also introduced which searches for trajectories which arc highly probable with respect lo a set of constraints and an M S P machine representation. Like human subjects, the model (i) recalls propositions with greater causal connectivity as retention interval is increased, and (ii) demonstrates how misordered propositions tend to "drift" more towards their canonical position in a text as retention interval is increased.