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 ...

[1]  J. Bransford,et al.  Sentence memory: A constructive versus interpretive approach ☆ ☆☆ , 1972 .

[2]  Marcia K. Johnson,et al.  Contextual prerequisites for understanding: Some investigations of comprehension and recall , 1972 .

[3]  Stephen A. Ritz,et al.  Distinctive features, categorical perception, and probability learning: some applications of a neural model , 1977 .

[4]  J. Mackie,et al.  The cement of the universe : a study of causation , 1977 .

[5]  Walter Kintsch,et al.  Toward a model of text comprehension and production. , 1978 .

[6]  Arthur C. Graesser,et al.  How to catch a fish: The memory and representation of common procedures∗ , 1978 .

[7]  Mandler JeanM..  A code in the node: The use of a story schema in retrieval , 1978 .

[8]  John B. Black,et al.  Scripts in memory for text , 1979, Cognitive Psychology.

[9]  A. Graesser,et al.  Answers to why-questions expose the organization of story plot and predict recall of actions , 1980 .

[10]  R. Spiro.  Accommodative reconstruction in prose recall. , 1980 .

[11]  F. Fairman.  Introduction to dynamic systems: Theory, models and applications , 1979, Proceedings of the IEEE.

[12]  R. Schank,et al.  Inside Computer Understanding , 1981 .

[13]  John B. Black,et al.  Causal coherence and memory for events in narratives , 1981 .

[14]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[15]  T. Trabasso.  Causal Cohesion and Story Coherence. , 1982 .

[16]  N. Cocchiarella,et al.  Situations and Attitudes. , 1986 .

[17]  J. Lucariello,et al.  Scripts and the Development of Memory , 1983 .

[18]  P. Johnson-Laird.  Mental models , 1989 .

[19]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[20]  T. Trabasso,et al.  Causal thinking and the representation of narrative events , 1985 .

[21]  Sharon Bischofshausen.  Developmental differences in schema dependency for temporally ordered story events , 1985 .

[22]  Geoffrey E. Hinton,et al.  A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..

[23]  T. Trabasso,et al.  Causal relatedness and importance of story events , 1985 .

[24]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[25]  Paul van den Broek,et al.  Causal networks versus goal hierarchies in summarizing text , 1986 .

[26]  R. Golden.  The :20Brain-state-in-a-box Neural model is a gradient descent algorithm , 1986 .

[27]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[28]  Richard Durbin,et al.  An analogue approach to the travelling salesman problem using an elastic net method , 1987, Nature.

[29]  Jeroen G. W. Raaijmakers.  A formal model for associative memory , 1987 .

[30]  J.F.A.K. van Benthem,et al.  "Situations, Language and Logic" , 1987 .

[31]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

[32]  C. Fletcher,et al.  Causal reasoning in the comprehension of simple narrative texts , 1988 .

[33]  P. Broek.  The effects of causal relations and hierarchical position on the importance of story statements , 1988 .

[34]  R. Miikkulainen,et al.  A modular neural network architecture for sequential paraphrasing of script-based stories , 1989, International 1989 Joint Conference on Neural Networks.

[35]  Peter Norvig,et al.  Marker Passing as a Weak Method for Text Inferencing , 1989, Cogn. Sci..

[36]  James L. McClelland,et al.  Sentence comprehension: A parallel distributed processing approach , 1989, Language and Cognitive Processes.

[37]  T. Trabasso,et al.  Logical necessity and transitivity of causal relations in stories , 1989 .

[38]  James L. McClelland,et al.  Learning and Applying Contextual Constraints in Sentence Comprehension , 1990, Artif. Intell..

[39]  G. Bower,et al.  Mental models in narrative comprehension. , 1990, Science.

[40]  P. Broek.  The causal inference maker: Towards a process model of inference generation in text comprehension. , 1990 .

[41]  Robert B. Allen,et al.  Connectionist Language Users , 1990 .

[42]  Risto Mukkulainen,et al.  Script Recognition with Hierarchical Feature Maps , 1990 .

[43]  Armen Gabrielian,et al.  HMS Machines: A Unified Framework for Specification, Verification and Reasoning for Real-Time Systems , 1991 .

[44]  Matthew K. Franklin,et al.  Multilevel specification of real time systems , 1991, CACM.

[45]  Michael I. Jordan.  Constrained supervised learning , 1992 .

[46]  Risto Miikkulainen,et al.  Script Recognition with Hierarchical Feature Maps , 1992 .

[47]  R. Golden.  Stability and optimization analyses of the generalized brain-state-in-a-box neural network model , 1993 .

[48]  David E. Rumelhart,et al.  Toward an interactive model of reading. , 1994 .

[49]  Richard M. Golden.  Making correct statistical inferences using a wrong probability model , 1995 .