Subsymbolic Parsing of Embedded Structures

Symbolic artificial intelligence is motivated by the hypothesis that symbol manipulation is both necessary and sufficient for intelligence [34]. Symbolic systems have been quite successful, for example, in modeling in-depth natural language processing [[13], [26], [43]], episodic memory [[22], [24], and problem solving [[23], [35], [36]]. In such systems, knowledge is encoded in terms of explicit symbolic structures, and processing is based on handcrafted rules that operate on these structures.

[1]  E. Feigenbaum,et al.  Computers and Thought , 1963 .

[2]  Charles J. Fillmore,et al.  THE CASE FOR CASE. , 1967 .

[3]  Emmon W. Bach,et al.  Universals in Linguistic Theory , 1970 .

[4]  M. Posner,et al.  Attention and cognitive control. , 1975 .

[5]  A. Caramazza,et al.  Dissociation of algorithmic and heuristic processes in language comprehension: Evidence from aphasia , 1976, Brain and Language.

[6]  Walter Schneider,et al.  Controlled and Automatic Human Information Processing: 1. Detection, Search, and Attention. , 1977 .

[7]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[8]  Roger C. Schank,et al.  Scripts, plans, goals and understanding: an inquiry into human knowledge structures , 1978 .

[9]  Wendy Grace Lehnert,et al.  The Process of Question Answering , 2022 .

[10]  Walter Anthony Cook.  Case Grammar Theory , 1979 .

[11]  Janet L. Kolodner,et al.  Retrieval and organizational strategies in conceptual memory: a computer model , 1980 .

[12]  Michael Lebowitz,et al.  Generalization and memory in an integrated understanding system , 1980 .

[13]  Allen Newell,et al.  Physical Symbol Systems , 1980, Cogn. Sci..

[14]  T. Shallice.  Specific impairments of planning. , 1982, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[15]  M. Dyer.  In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension , 1983 .

[16]  M. Huang.  A Developmental Study of Children's Comprehension of Embedded Sentences with and without Semantic Constraints , 1983 .

[17]  R. Shiffrin,et al.  Automatic and controlled processing revisited. , 1984, Psychological review.

[18]  G. Logan.  On the ability to inhibit thought and action , 1984 .

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

[20]  James L. McClelland,et al.  Mechanisms of Sentence Processing: Assigning Roles to Constituents of Sentences , 1986 .

[21]  James L. McClelland,et al.  Parallel Distributed Processing: Explorations in the Microstructure of Cognition : Psychological and Biological Models , 1986 .

[22]  Donald A. Norman,et al.  Attention to Action , 1986 .

[23]  Geoffrey E. Hinton,et al.  A general framework for parallel distributed processing , 1986 .

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

[25]  Robert B. Allen,et al.  Several Studies on Natural Language ·and Back-Propagation , 1987 .

[26]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[27]  Allen Newell,et al.  GPS, a program that simulates human thought , 1995 .

[28]  T. Shallice.  From Neuropsychology to Mental Structure , 1988 .

[29]  N. Cowan.  Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information-processing system. , 1988, Psychological bulletin.

[30]  Mark C. Detweiler,et al.  A Connectionist/Control Architecture for Working Memory , 1988 .

[31]  Cynthia L. Cosic,et al.  Learning to Represent and Understand Locative Prepositional Phrases , 1988 .

[32]  P. Smolensky.  On the proper treatment of connectionism , 1988, Behavioral and Brain Sciences.

[33]  James L. McClelland,et al.  Learning Subsequential Structure in Simple Recurrent Networks , 1988, NIPS.

[34]  C. P. Dolan.  Tensor manipulation networks: connectionist and symbolic approaches to comprehension, learning, and planning , 1989 .

[35]  David S. Touretzky.  Connectionism and Compositional Semantics , 1989 .

[36]  W. Freeman.  Second Commentary: On the proper treatment of connectionism by Paul Smolensky (1988) - Neuromachismo Rekindled , 1989 .

[37]  R. Pfeifer,et al.  Connectionism in Perspective , 1989 .

[38]  Paul Smolensky,et al.  Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems , 1990, Artif. Intell..

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

[40]  Michael G. Dyer,et al.  Learning Distributed Representations of Conceptual Knowledge and their Application to Script-based Story Processing , 1990 .

[41]  Robert F Simmons,et al.  Training a Neural Network to be a Context Sensitive Grammar , 1990 .

[42]  A. Newell.  Unified Theories of Cognition , 1990 .

[43]  Jeffrey L. Elman,et al.  Finding Structure in Time , 1990, Cogn. Sci..

[44]  Jordan B. Pollack,et al.  Recursive Distributed Representations , 1990, Artif. Intell..

[45]  Geoffrey E. Hinton.  Mapping Part-Whole Hierarchies into Connectionist Networks , 1990, Artif. Intell..

[46]  Risto Miikkulainen,et al.  A Pdp Architecture for Processing Sentences With Relative Clauses , 1990, COLING.

[47]  David J. Chalmers,et al.  Syntactic Transformations on Distributed Representations , 1990 .

[48]  Risto Miikkulainen,et al.  Natural Language Processing With Modular PDP Networks and Distributed Lexicon , 1991, Cogn. Sci..

[49]  Lonnie Chrisman,et al.  Learning Recursive Distributed Representations for Holistic Computation , 1991 .

[50]  Ajay N. Jain.  Parsing Complex Sentences with Structured Connectionist Networks , 1991, Neural Computation.

[51]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[52]  Jeffrey L. Elman,et al.  Distributed Representations, Simple Recurrent Networks, and Grammatical Structure , 1991, Mach. Learn..

[53]  Paul W. Munro,et al.  A Network for Encoding, Decoding and Translating Locative Prepositions , 1991 .

[54]  Mark F. St. John,et al.  The Story Gestalt: A Model of Knowledge-Intensive Processes in Text Comprehension , 1992, Cogn. Sci..

[55]  Douglas S. Blank,et al.  Exploring the Symbolic/Subsymbolic Continuum: A case study of RAAM , 1992 .

[56]  John Dinsmore,et al.  The symbolic and connectionist paradigms : closing the gap , 1992 .

[57]  George Berg,et al.  A Connectionist Parser with Recursive Sentence Structure and Lexical Disambiguation , 1992, AAAI.

[58]  Risto Miikkulainen,et al.  Subsymbolic natural language processing - an integrated model of scripts, lexicon, and memory , 1993, Neural network modeling and connectionism.