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Director of the IGERT program		Paul Smolensky
			Research Area
			Research Summary
			Courses
			Education
			Professional Positions
			Professional Awards
			Professional Service
			List of Publications
			Grants
			Professional Activities
			Contact Information
			CV in pdf format
	smolensky@cogsci.jhu.edu Phone: 6-5114 Office: Krieger 241B
			* Principles of Dave's Philosophy. Celebration honoring the career of David Rumelhart. Carnegie-Mellon University, October, 1999.

Research Area
Primary: Universal grammar -- Optimality Theory: phonology, syntax, acquisition, learnability, processing.
Secondary: Integration of connectionist ('neural') and symbolic computation: computational, linguistic, and philosophical issues.

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Research Summary

My research program is motivated by a fundamental paradox lurking in the study of cognition. When we develop precise theories of higher cognitive domains like language and reasoning, we rely crucially on complex symbolic rule systems like those of grammar and logic. According to traditional cognitive science and artificial intelligence, such symbolic systems are the very essence of higher intelligence. Yet we believe intelligence resides in the brain, where computation appears to be numerical, not symbolic; parallel, not serial; rather distributed, not as highly localized as in symbolic systems. Furthermore, when observed carefully, much of human behavior is remarkably sensitive to the statistical aspect of experience; hard-edged rule systems seem ill-equipped to handle these subtleties. Thus a unified theory of cognition must assign the proper roles to symbolic computation, numerical neural computation, and statistical computation.

More specifically, the questions driving that research are these. What are the central general principles of computation in connectionist -- abstract neural -- networks? How can these principles be reconciled with those of symbolic computation? This work has led to a new computational architecture for cognition which integrates connectionist and symbolic computation. Can this framework further the theory of higher cognition, by connecting it with lower-level principles derived from neural computation?

With Alan Prince I have developed a grammatical formalism called Optimality Theory which brings certain general connectionist computational principles into the symbolic theory of universal grammar. The connectionist conception of intuitive knowledge as a collection of conflicting soft constraints, interacting via optimization of well-formedness or 'Harmony,' combines with structured representations and universal constraints from symbolic linguistic theory. The optimization that emerges is not inherently numerical, as constraint strengths are encoded in a hierarchy of constraints, ranked from strongest to weakest; each constraint is stronger than all weaker constraints combined.

According to Optimality Theory, possible human languages share a common set of universal constraints on well-formedness. These constraints are highly general, and hence conflict; so some must be violated in optimal, i.e., grammatical, structures. The different surface patterns of the world's languages emerge via different priority rankings of the universal constraints: each ranking is a language-particular grammar, a means of resolving the inherent conflicts among the universal constraints.

My current research addresses multiple aspects of Optimality Theory (OT). These include superadditive constraint interaction ('local conjunction' of constraints), especially in phonology (vowel harmony; Obligatory Contour Principle; sonority and syllable structure), as well as numerical and connectionist implementation of OT constraint interaction. Much of my OT research is collaborative, as indicated in the following table of current and recent collaborative research.

 

Collaborator	Department	Research topic
Prof. Laura Benua	Linguistics, U Maryland	Phonology: Markedness in vowel harmony
Prof. Colin Wilson (former Ph.D. advisee)	Linguistics, UCLA	An OT theory of syntactic interpretation (recoverability, ineffability, ambiguity)
Matt Goldrick*	Cognitive Science, Hopkins	Enriching OT phonological representations to meet the challenge of phonological opacity
Prof. Alan Penczek (former Ph.D. student)	Philosophy, Villa Julie	OTsemantics for causal efficacy
Prof. Suzanne Stevenson	Computer Science, Toronto	OT theory of on-line human sentence processing
Prof. Peter Jusczyk	Psychology, Hopkins	Experimental studies of the development of phonological knowledge in infants, with OT analysis
Lisa Davidson*	Cognitive Science, Hopkins	Experimental studies of final L1 and initial L2 phonological grammars, with OT analysis
Matt Goldrick* Prof. Brenda Rapp	Cognitive Science, Hopkins	OT grammars and phonological deficits in aphasia
Melanie Soderstrom* Dr. Donald Mathis	Psychology, Hopkins Cognitive Science, Hopkins	'Abstract genomic encoding' of universal grammar in OT
John Hale*	Cognitive Science, Hopkins	Connectionist parsers for OT/Harmonic Grammars
Prof. Bruce Tesar (former Ph.D. advisee)	Linguistics, Rutgers	Learnability of OT grammars

*current Ph.D. students

Prospective graduate students with serious interests in linguistics who are potentially interested in any of my current research topics are encouraged to contact me and to consider our Ph.D. Program in Cognitive Science .

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Courses

• 050.109 Minds, Brains & Computers
• 050.325 Sound Structure in Natural Language
• 050.326 Foundations of Cognitive Science
• 050.327 Advanced Topics in Sound Structure
• 050.372 Formal Methods in Cognitive Science: Neural Networks
• 050.625 Sound Structure in Natural Language
• 050.626 Foundations of Cognitive Science
• 050.627 Advanced Topics in Sound Structure
• 050.672 Formal Methods in Cognitive Science: Neural Networks
• 050.823 Research Seminar in Sound Structure
• 050.830 Topics in Cognitive Science

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Education

• Ph.D. in mathematical physics, Indiana University, 1981.
• M.S. in physics, Indiana University, 1977.
• A.B. summa cum laude in physics, Harvard University, 1976.

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Professional Positions

• Chair, Department of Cognitive Science, Johns Hopkins University, Jan. 1997 - June 1998 (Acting), July 1998 - June 2000.
• Full Professor, Department of Cognitive Science, Johns Hopkins University, 1994-present.
• Adjunct Professor, Department of Linguistics, University of Maryland at College Park, 1994-present.
• Faculty, Center for the History and Philosophy of Science, Johns Hopkins University, 1995-present.
• Assistant Director, Center for Language and Speech Processing, Johns Hopkins University, 1995-present.
• Director, NSF IGERT Training Program in the Cognitive Science of Language, 1999-2004.
  
  
• Professor, Department of Computer Science, University of Colorado at Boulder,
  Full Professor, 1994-95 (on leave, 1994-95).
  Associate Professor, 1990-94.
  Assistant Professor, 1985-90.
  
  
• Assistant Research Cognitive Scientist (Assistant Professor - Research), Institute for Cognitive Science, University of California at San Diego, 1982-85.
• Visiting Scholar, Program in Cognitive Science, University of California at San Diego, 1981-82.
• Faculty, Summer School in Linguistics, Girona, Spain, 2000.
• Faculty, First International Summer Institute in Cognitive Science, SUNY Buffalo, 1994.

• Faculty, Linguistic Institute, University of California at Santa Cruz, 1991.
• Faculty, Connectionist Models Summer School; Carnegie-Mellon University, 1986, 1988; University of California, San Diego, 1990; University of Colorado, Boulder, 1993.
• Faculty, Advanced Course in Artificial Intelligence, Neuchâtel, Switzerland, 1989.
• Consultant, Xerox Palo Alto Research Center, Intelligent Systems Laboratory, 1987.
  
• Visiting Scholar, Linguistic Institute, Stanford University, 1987.
  
  
• National Science Foundation, John H. Edwards, and Indiana University Graduate Fellow, 1976-81.
• Associate Instructor, Department of Physics, Indiana University, 1976-81.
• Project Specialist, Institute for Research on Poverty, University of Wisconsin, 1978.
• Consultant, California Planning and Conservation Foundation, 1975.
• Undergraduate Teaching Assistant, Committee on Natural Sciences, Harvard University, 1974-75.

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Professional Awards

• Teaching Award Nomination, for 'Minds, Brains and Computers,' Cognitive Science 109, and 'Advanced Topics in Sound Structure,' 1998.
• Guggenheim Foundation Fellowship, 1995-96.
• Faculty Fellowship, University of Colorado, 1991-92.
• Visiting Scholarship, Program in Cognitive Science, University of California at San Diego, 1981-82.
• John H. Edwards Fellowship ("the most highly prized graduate fellowship awarded directly by Indiana University"), 1980-81.
• Lieber Associate Instructor Award (6 awarded annually system-wide), Indiana University, 1979.
• Associate Instructor Teaching Award, Physics Department, Indiana University, 1978.
• National Science Foundation Graduate Fellowship in Mathematical Physics, 1977-80. Indiana University Department of Physics Graduate Fellowship, 1976-80.
• A.B. with honors in physics, Harvard University; among top five graduates of 1976.
• Master's Award, Dudley House, Harvard University, 1976.
• Detur Prize, Harvard University, 1975.
• Phi Beta Kappa membership, Harvard College chapter, 1975.
• John Harvard Scholarship, Harvard University, 1973-74, 1974-75.
• Edwards Whitaker Scholarship, Harvard University, 1974.

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Professional Service

• President, Society for Philosophy and Psychology. 2000 - 01.
• President, Cognitive Science Society. 1995 - 96, 1996 - 97.
• Annual Conference Oversight Committee, Cognitive Science Society. 1995 - 98.
• Governing Board, Cognitive Science Society. 1992 - 98.
• Executive Board, Society for Philosophy and Psychology. 1988 - 91, 1994 - 97.
• International Advisory Board, Cognitive Science Department, New Bulgarian University. 1993 - present.
  
  
• Editorial Board, Minds and Machines: Journal for Artificial Intelligence, Philosophy, and Cognitive Science. 1990 - present.
• Editorial Board, Cognitive Science. 1988 - present.
• Editorial Board, Connection Science: A Journal of Neural Computing, Artificial Intelligence, and Cognitive Research. 1988 - present.
  
  
• Advisory Board, Neural Network Series, MIT Press. 1990 - present.
• Advisory Editorial Board, Network: Computation in Neural Systems. 1989 - 91.
  
  
• Organizer, Symposium, Many languages -- One grammar: The mathematics of universal grammar in Optimality Theory. Annual Meeting of the American Association for the Advancement of Science, San Francisco, CA, February 2001.
• Program Committee, Cognitive Science Society Conference, University of Pennsylvania, August 2000.
• Organizing Committee, Cognitive Science Society Conference, Stanford, CA, July 1997.
• Organizer, Symposium on Connectionism and Language, Annual Meeting of the American Association for the Advancement of Science, Baltimore, MD, February 1996.
• Program Committee, Association for Computational Linguistics Conference, Cambridge, MA, June 1995.
• Organizer, Symposium on Connectionism and Cognitive Science, First International Summer Institute in Cognitive Science, Buffalo, NY, July 1994.
• Organizing Committee, Cognitive Science Society Conference, Boulder, CO, June 1993.
• Organizing Committee, Connectionist Models Summer School, Boulder, CO, June 1993.
• Honorary Organizing Committee, Neural Networks Symposium, International Symposia on Information Sciences, Iizuka, Kyushu, Japan, July, 1992.

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List of Publications

Books

1. Smolensky, P., & Legendre, G. To appear. Architecture of the mind/brain: Neural network theory, optimality, and universal grammar in cognitive science. (Ms. 850 pp.)
2. Prince, A. & Smolensky, P. To appear. Optimality Theory: Constraint interaction in generative grammar. Linguistic Inquiry Monograph Series, MIT Press. (Ms. 243 pp.)
3. Tesar, B. & Smolensky, P. 2000. Learnability in Optimality Theory. MIT Press.
4. Smolensky, P., Mozer, M. C., & Rumelhart, D. E. (eds.). 1996. Mathematical perspectives on neural networks. Lawrence Erlbaum Publishers.
5. Macdonald, C. & Macdonald, G. (eds.). 1995. Connectionism: Debates on psychological explanation, Volume 2. Basil Blackwell. [Contributed 4 chapters, 183 of 412 pp.]
6. Mozer, M.C., Smolensky, P., Touretzky, D., Elman, J., & Weigend, A. (eds.). 1993. Proceedings of the Connectionist Models Summer School 1993.Lawrence Erlbaum Publishers.
7. Smolensky, P. 1992. Il Connessionismo: Tra simboli e neuroni. Italian translation of the entire treatment, including peer commentary: On the proper treatment of connectionism, Behavioral and Brain Sciences, 11, 1-74; with introduction by Marcello Frixione. Genova: Marietti/Cambridge University Press.

Grammar (ROA = http://ruccs.rutgers.edu/roa.html, the Rutgers Optimality Archive)

8. Jusczyk, P., Smolensky, P., and Allocco, T. How English-learning infants respond to markedness and faithfulness constraints. Under review.
9. Smolensky, P. To appear. Learnability, the initial state, and 'richness of the base' in Optimality Theory. Linguistic Inquiry.
10. Smolensky, P. 2000. Grammar-based connectionist approaches to language. Cognitive Science 23: 589-613. Reprinted in M. Christiansen and N. Chater. 2000. Connectionist Psycholinguistics. Ablex.
11. Tesar, B. & Smolensky, P. 1998. Learning Optimality-Theoretic grammars. Lingua, 106: 161-196. Reprinted in Sorace, A., Heycock, C. and Shillcock, R. (eds.) Language Acquisition: Knowledge Representation and Processing. Amsterdam: Elsevier.
12. Legendre, G., Smolensky, P., & Wilson, C. 1998. When is less more? Faithfulness and minimal links in wh-chains. In Pilar Barbosa, Danny Fox, Paul Hagstrom, Martha McGinnis, and David Pesetsky, eds., Is the Best Good Enough? Optimality and Competition in Syntax. MIT Press. 249-289
13. Tesar, B. & Smolensky, P. 1998. Learnability in Optimality Theory. Linguistic Inquiry, 29: 229-268
14. Prince, A. & Smolensky, P. 1997. Optimality: From neural networks to universal grammar. Science 275: 1604-1610.
15. Smolensky, P. 1996. On the comprehension/production dilemma in child language. Linguistic Inquiry 27: 720-731. ROA-118.
16. Legendre, G., Smolensky, P., & Wilson, C. 1996. When is less more? Faithfulness and minimal links in wh-chains. Technical Report JHU-CogSci-96-7, Cognitive Science Department, Johns Hopkins University. ROA-117. Published as [12].
17. Smolensky, P. 1996. The initial state and 'richness of the base' in Optimality Theory. Technical Report JHU-CogSci-96-4, Cognitive Science Department, Johns Hopkins University. ROA-154. Revision published as [9].
18. Tesar, B. & Smolensky, P. 1996. Learnability in Optimality Theory (long version). Technical Report JHU-CogSci-96-3, Cognitive Science Department, Johns Hopkins University, Baltimore, Md. ROA-156. Excerpts, revised, published as [11].
19. Tesar, B. & Smolensky, P. 1996. Learnability in Optimality Theory (short version). Technical Report JHU-CogSci-96-2, Cognitive Science Department, Johns Hopkins University, Baltimore, Md. ROA-155. Revision published as [13].
20. Legendre, G., Wilson, C., Smolensky, P., Homer, K., & Raymond, W. 1995. Optimality in wh-chains. University of Massachusetts Occasional Papers in Linguistics 18: Papers in Optimality Theory, J. Beckman, S. Urbanczyk, & L. Walsh, eds. Amherst, MA: GLSA, University of Massachusetts. 607-636. ROA-85.
21. Smolensky, P. 1995. On the structure of Con, the constraint component of UG. Handout of talk at UCLA, April 7. ROA-86
22. Tesar, B. & Smolensky, P. 1994. The learnability of Optimality Theory. Proceedings of the West Coast Conference on Formal Linguistics XIII. 122-137.
23. Tesar, B. & Smolensky, P. 1993. The learnability of Optimality Theory: An algorithm and some basic complexity results. Technical Report CU-CS-678-93, Department of Computer Science, University of Colorado at Boulder. October. ROA-2. Expanded to [18].
24. Prince, A. & Smolensky, P. 1993. Optimality Theory: Constraint interaction in generative grammar. Technical Report CU-CS-696-93, Department of Computer Science, University of Colorado at Boulder, and Technical Report TR-2, Rutgers Center for Cognitive Science, Rutgers University, New Brunswick, NJ. April. (234 pages). To appear as [2].
25. Smolensky, P. 1993. Harmony, markedness, and phonological activity. Handout of keynote address, Rutgers Optimality Workshop-1, October 23. ROA-87.
26. Legendre, G., Raymond, W., & Smolensky, P. 1993. An Optimality-Theoretic typology of case and grammatical voice systems. Proceedings of the Nineteenth Annual Meeting of the Berkeley Linguistics Society. Berkeley, CA. February. 464-478. ROA-3.
27. Legendre, G., Miyata, Y., & Smolensky, P. 1991. Unifying syntactic and semantic approaches to unaccusativity: A connectionist approach. In L. Sutton & C. Johnson (with Ruth Shields) (Eds.), Proceedings of the Seventeenth Annual Meeting of the Berkeley Linguistics Society. Berkeley, CA. February. 156-167.
28. Prince, A. & Smolensky, P. 1991. Notes on Connectionism and Harmony Theory in Linguistics. Technical Report CU-CS-533-91, Department of Computer Science, University of Colorado at Boulder. July. [Notes from the course, 'Connectionism and Harmony Theory in Linguistics,' LSA Linguistic Institute, University of California, Santa Cruz; July, 1991.] Optimality Theory part expanded to [24].
29. Smolensky, P. 1991. Connectionism. In W. Bright (Ed.) The International Encyclopedia of Linguistics. Oxford University Press. 294-297.
30. Legendre, G., Miyata, Y., & Smolensky, P. 1990. Can connectionism contribute to syntax? Harmonic Grammar, with an application. Proceedings of the 26th Meeting of the Chicago Linguistic Society. Chicago, IL. April.
31. Legendre, G., Miyata, Y., & Smolensky, P. 1990. Harmonic Grammar - A formal multi-level connectionist theory of linguistic well-formedness: An application. Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, Cambridge, MA. July. 884-891.
32. Legendre, G., Miyata, Y., & Smolensky, P. 1990. Harmonic Grammar - A formal multi-level connectionist theory of linguistic well-formedness: Theoretical foundations. Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, Cambridge, MA. July. 388-395.

Computation

33. Smolensky, P. (1996). Computational, dynamical, and statistical perspectives on the processing and learning problems in neural network theory. In Smolensky, P., Mozer, M. C., & Rumelhart, D. E. (Eds.). Mathematical Perspectives on Neural Networks. Mahwah, NJ: Lawrence Erlbaum Publishers. 1-15.
34. Smolensky, P. (1996). Computational perspectives on neural networks. In Smolensky, P., Mozer, M. C., & Rumelhart, D. E. (Eds.). Mathematical Perspectives on Neural Networks. Mahwah, NJ: Lawrence Erlbaum Publishers. 17-40.
35. Smolensky, P. (1996). Dynamical perspectives on neural networks. In Smolensky, P., Mozer, M. C., & Rumelhart, D. E. (Eds.). Mathematical Perspectives on Neural Networks. Mahwah, NJ: Lawrence Erlbaum Publishers. 245-270.
36. Smolensky, P. (1996). Statistical perspectives on neural networks. In Smolensky, P., Mozer, M. C., & Rumelhart, D. E. (Eds.). Mathematical Perspectives on Neural Networks. Mahwah, NJ: Lawrence Erlbaum Publishers. 453-496.
37. Tesar, B. & Smolensky, P. (1994). Synchronous-firing variable binding is spatio-temporal tensor product representation. Proceedings of the 16th Annual Conference of the Cognitive Science Society. Atlanta, GA. August.
38. Smolensky, P. (1993). Harmonic Grammars for formal languages. In S. Hanson, J. D. Cowan, & C. L. Giles, (Eds.), Advances in Neural Information Processing Systems 5, San Mateo, CA: Morgan Kaufmann. [Collected papers of the IEEE Conference on Neural Information Processing Systems-Natural and Synthetic, Denver, Nov. 1992.] 847-854.
39. Miyata, Y, Smolensky, P., & Legendre, G. (1993). Distributed representation and parallel processing of recursive structures. Proceedings of the 15th Annual Conference of the Cognitive Science Society, Boulder, CO. June. 759-764.
40. Wagner, K., Mozer, M., Smolensky, P., Miyata, Y., Fellows, M. (1993). Optical neural networks using a new radial nonlinear neural layer. Proceedings of the SPIE (Society of Photo-Optical Instrumentation Engineers), 1773A-10.
41. McMillan, C., Mozer, M., & Smolensky, P. (1993). Dynamic conflict resolution in a connectionist rule-based system. Proceedings of the 13th International Joint Conference on Artificial Intelligence, 1366-1371. San Mateo, CA: Morgan Kauffmann.
42. McMillan, C., Mozer, M., & Smolensky, P. (1992). Rule induction through integrated symbolic and subsymbolic processing. In J. Moody, S. Hanson, & R. Lippman, (Eds.), Advances in Neural Information Processing Systems 4. San Mateo, CA: Morgan Kaufmann. [Collected papers of the IEEE Conference on Neural Information Processing Systems-Natural and Synthetic, Denver, Nov. 1991.] 969-976.
43. Smolensky, P. (1992). Integrated connectionist/symbolic computation and formal languages. Proceedings of the International Symposia on Information Sciences. Iizuka, Kyushu, Japan. July. 42-49.
44. Legendre, G., Miyata, Y., & Smolensky, P. (1991). Distributed recursive structure processing. In Touretzky, D. S., Lippman, R. (Eds.), Advances in Neural Information Processing Systems 3. San Mateo, CA: Morgan Kaufmann. [Collected papers of the IEEE Conference on Neural Information Processing Systems-Natural and Synthetic, Denver, Nov. 1990.] 591-597. Slightly expanded version in Mayoh, B. (Ed.), Scandinavian Conference on Artificial Intelligence-91, 47-53. Amsterdam: IOS Press.
45. McMillan, C., Mozer, M. C., & Smolensky, P. (1991). The connectionist scientist game: Rule extraction and refinement in a neural network. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society, Chicago, IL. July.
46. McMillan, C., Mozer, M., & Smolensky, P. (1991). Learning explicit rules in a neural network. Proceedings of the International Joint Conference on Neural Networks. Seattle, WA. July.
47. Smolensky, P. (1990). Tensor product variable binding and the representation of symbolic structures in connectionist networks. Artificial Intelligence, 46, 159-216. [Reprinted in G. Hinton, (Ed.), (1990), Connectionist symbol processing, Elsevier/MIT Press.]
48. Brousse, O. & Smolensky, P. (1990). Connectionist generalization and incremental learning in combinatorial domains. In H. Haken (Ed.), Synergetics of Cognition. Springer-Verlag. 70-80.
49. Smolensky, P. (1990). Representation in connectionist networks. Intellectica: The Journal of the French Association for Cognitive Research, 9-10, 127-165.
50. Brousse, O. & Smolensky, P. (1990). Interference and generalization in connectionist networks: Within-domain structure or between-domain correlation? - A response, Neural Network Review, 4, 29.
51. Mozer, M. C., & Smolensky, P. (1989). Using relevance to reduce network size automatically. Connection Science, 1, 3-16.
52. Dolan, C. & Smolensky, P. (1989). Tensor Product Production System: A modular architecture and representation. Connection Science, 1, 53-68.
53. Mozer, M. C., & Smolensky, P. (1989). Skeletonization: Trimming the fat from a network via relevance assessment. In D. S. Touretzky (Ed.), Advances in Neural Information Processing Systems 1. San Mateo, CA: Morgan Kaufmann. [Collected papers of the IEEE Conference on Neural Information Processing Systems-Natural and Synthetic, Denver, Nov. 1988.] 107-115.
54. Brousse, O. & Smolensky, P. (1989). Virtual memories and massive generalization in connectionist combinatorial learning. Proceedings of the Eleventh Annual Meeting of the Cognitive Science Society. Ann Arbor, MI. August. 380-387.
55. Smolensky, P. (1988). Analysis of distributed representation of constituent structure in connectionist systems. Proceedings of Neural Information Processing Systems-87. Denver, CO. November. 730-739.
56. Bein, J. & Smolensky, P. (1988). Application of the interactive activation model to document retrieval. Proceedings of Neuro-Nîmes 1988: Neural networks and their applications. Nîmes, France. November. 295-308.
57. McMillan, C. & Smolensky, P. (1988). Analyzing a connectionist model as a system of soft rules. Proceedings of the Tenth Annual Meeting of the Cognitive Science Society. Montreal, Canada. August. 62-68.
58. Dolan, C. & Smolensky, P. (1988). Implementing a connectionist production system using tensor products. In D. Touretzky, G. E. Hinton, & T. J. Sejnowski (Eds.), Proceedings of the Connectionist Models Summer School, 1988. Morgan Kaufmann. 265-272.
59. Smolensky, P. (1987). On variable binding and the representation of symbolic structures in connectionist systems. Technical Report CU-CS-355-87, Department of Computer Science, University of Colorado at Boulder. February.
60. Smolensky, P. (1986). Formal modeling of subsymbolic processes: An introduction to harmony theory. In N. E. Sharkey (Ed.), Directions in the Science of Cognition. London: Horwoods. 204-235.
61. Smolensky, P. (1986). Information processing in dynamical systems: Foundations of harmony theory. In D. E. Rumelhart, J. L. McClelland, & the PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations. Cambridge, MA: MIT Press/Bradford Books. 194-281.
62. Smolensky, P. (1986). Neural and conceptual interpretations of parallel distributed processing models. In J. L. McClelland, D. E. Rumelhart, & the PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 2: Psychological and Biological Models. Cambridge, MA: MIT Press/Bradford Books. 390-431.
63. Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. E. (1986). Schemata and sequential thought processes in parallel distributed processing. J. L. McClelland, D. E. Rumelhart, & the PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 2: Psychological and Biological Models. Cambridge, MA: MIT Press/Bradford Books. 7-57. [Reprinted in A. Collins & E. Smith (Eds), 1988, Readings in Cognitive Science, San Mateo, CA: Morgan Kaufmann.]
64. Smolensky, P. (1984). The mathematical role of self-consistency in parallel computation. Proceedings of the Sixth Annual Conference of the Cognitive Science Society. Boulder, CO. June. 319-325.
65. Riley, M. S. & Smolensky, P. (1984). A parallel model of (sequential) problem solving. Proceedings of the Sixth Annual Conference of the Cognitive Science Society. Boulder, CO. June. 286-292.
66. Smolensky, P. (1984). Harmony theory: thermal parallel models in a computational context. In P. Smolensky & M. S. Riley, Harmony theory: Problem solving, parallel cognitive models, and thermal physics, Technical Report 8404. Institute for Cognitive Science, University of California at San Diego. April.
67. Hinton, G. E. & Smolensky, P. (1984). Parallel computation and the mass-spring model of motor control. Report 123. Center for Human Information Processing, University of California at San Diego. June.
68. Smolensky, P. (1983). Schema selection and stochastic inference in modular environments. Proceedings of the National Conference on Artificial Intelligence. Washington, DC. August. 378-382.

Foundations

69. Smolensky, P. (1995). Constituent structure and explanation in an integrated connectionist/symbolic cognitive architecture. In C. Macdonald & G. Macdonald (Eds.). Connectionism: Debates on Psychological Explanation, Volume 2. 221-290. Oxford: Basil Blackwell.
70. [69] Smolensky, P. (1995). On the projectable predicates of connectionist psychology: A case for belief. In C. Macdonald & G. Macdonald (Eds.). Connectionism: Debates on Psychological Explanation, Volume 2. 357-394. Oxford: Basil Blackwell.
71. Smolensky, P. (1994). Computational theories of mind. In S. Guttenplan (Ed.), A Companion to the Philosophy of Mind. Blackwell Publishers. 176-185.
72. Smolensky, P. (1991). Connectionism, constituency, and the language of thought. In B. Loewer & G. Rey (Eds.), Meaning in Mind: Fodor and his Critics. Oxford: Basil Blackwell. 201-227. [Reprinted in C. Macdonald & G. Macdonald (Eds.), (1995), Connectionism: Debates on Psychological Explanation, Volume 2, Oxford: Basil Blackwell.]
73. Smolensky, P. (1990). Connectionism and the foundations of AI. In D. Partridge & Y. Wilks (Eds.), The Foundations of Artificial Intelligence: A Sourcebook. Cambridge: Cambridge University Press. 306-326.
74. Smolensky, P. (1989). Connectionism and constituent structure. In R. Pfeifer, Z. Schreter, F. Fogelman, & L. Steels (Eds.), Connectionism in Perspective. Amsterdam: Elsevier. 3-24.
75. Smolensky, P. (1989). Connectionist modeling: Neural computation/mental connections. In L. Nadel (Ed.), P. Culicover, L. A. Cooper, R. M. Harnish (Assoc. Eds.), Neural connections, mental computation. Cambridge, MA: MIT Press/Bradford. 49-67. [Reprinted in J. Haugeland, (Ed.). (1997). Mind Design II: Philosophy, Psychology, Artificial Intelligence, MIT Press/Bradford Books.]
76. Smolensky, P. (1987). On the connectionist reduction of conscious rule interpretation. Proceedings of the Ninth Conference of the Cognitive Science Society. Seattle, WA. July. 187-94.
77. Smolensky, P. (1987). The constituent structure of connectionist mental states: A reply to Fodor and Pylyshyn. Southern Journal of Philosophy, 26 (Supplement), 137-63. [Reprinted in T. Horgan & J. Tienson (Eds.), (1991), Connectionism and the Philosophy of Mind, Dordrecht: Kluwer Academic. 281-308; Spanish translation in E. Rabossi (Ed.), Filosofía y Ciencia Cognitiva, Buenos Aires-Barcelona: Editorial Paidós.]

    Integrative

78. Smolensky, P., Legendre, G., & Miyata, Y. (1993). Integrating connectionist and symbolic computation for the theory of language. Current Science 64, 381-391. Reprinted in: V. Honavar & L. Uhr, Artificial Intelligence and Neural Networks: Steps Toward Principled Integration, 509-530. Academic Press.
79. Smolensky, P., Legendre, G., & Miyata, Y. (1992). Principles for an Integrated Connectionist/Symbolic Theory of Higher Cognition. Technical Report CU-CS-600-92, Department of Computer Science and 92-8, Institute of Cognitive Science. University of Colorado at Boulder. (75 pages). Expanded to [2].
80. McNaughton, B. L. & Smolensky, P. (1991). Connectionist and neural modeling: Converging in the hippocampus. In R. G. Lister & H. J. Weingartner (Eds.), Perspectives on Cognitive Neuroscience. Oxford University Press. 93-109.
81. Smolensky, P. (1990). In defense of PTC: Reply to continuing commentary. Behavioral and Brain Sciences. 13, 407-411.
82. Smolensky, P. (1988). Putting Together Connectionism-again. Behavioral and Brain Sciences, 11, 59-74.
83. Smolensky, P. (1988). On the proper treatment of connectionism. Behavioral and Brain Sciences, 11, 1-23. [Reprinted in D. Cole, J. Fetzer, & T. Rankin (Eds.), (1990), Philosophy, Mind, and Cognitive Inquiry, Dordrecht: Kluwer Academic; A. I. Goldman, (1994), Readings in Philosophy and Cognitive Science, Cambridge: MIT Press/Bradford Books; and C. Macdonald & G. Macdonald (Eds.), (1995), Connectionism: Debates on Psychological Explanation, Volume 2, Oxford: Basil Blackwell; Italian translation published as monograph, Il connessionismo [7]; Hungarian translation in A Cognitive Science Reader, Budapest: Osiris Publishing House. (1997)]
84. Smolensky, P. (1987). Connectionist AI, symbolic AI, and the brain. Artificial Intelligence Review, 1, 95-109. [French translation with added post scriptum in D. Andler, (Ed.). (1992). Introduction aux sciences cognitives, Editions Gallimard.]
85. Smolensky, P. (1987). Connectionism and implementation: Commentary on J. R. Anderson, Methodologies for studying human knowledge. Behavioral and Brain Sciences, 10.

Others

86. Bernstein, B., Smolensky, P., & Bell, B. (1989). Design of a constraint-based hypertext system to augment human reasoning. Proceedings of the Rocky Mountain Conference on Artificial Intelligence. Denver, CO. June.
87. Smolensky, P., Fox, B., King, R., Lewis, C. (1988). Computer-aided reasoned discourse, or, How to argue with a computer. In R. Guindon (Ed.), Cognitive Science and Its Applications For Human-Computer Interaction. Hillsdale, NJ: Erlbaum. 109-62.
88. Smolensky, P. (1988). A design for Hype: A hypertext system for oral presentations. Technical Report, Xerox Palo Alto Research Center, Intelligent Systems Laboratory. February.
89. Smolensky, P., Bell, B., Fox, B., King, R., & Lewis, C. (1987). Constraint-based hypertext for argumentation. Proceedings of Hypertext-87. Chapel Hill, NC. November. 215-245.
90. Smolensky, P., Monty, M. L. & Conway, E. (1984). Formalizing task descriptions for command specification and documentation. Proceedings of the International Federation of Information Processing Conference on Human-Computer Interaction. London, England. September. 603-609.
91. Greenspan, S. & Smolensky, P. (1984). DESCRIBE: Environments for Specifying Commands and Retrieving Information By Elaboration. In User centered system design, Part II, Technical Report No. 8402. Institute for Cognitive Science, University of California at San Diego. March.
92. O'Malley, C., Smolensky, P, Bannon, L., Conway, E., Graham, J., Sokolov, J., & Monty, M. L. (1983). A proposal for user centered system documentation. Proceedings of the CHI 1983 Conference on Human Factors in Computing Systems. Boston, MA. December.
93. Freedman, B., Smolensky, P, & Weingarten, D. H. (1982). Monte Carlo evaluation of the continuum limit of (j4)4 and (j4)3 field theory. Physics Letters B, 113, 481-486.
94. Smolensky, P. (1981). Lattice Renormalization of j4 Theory. Doctoral thesis in mathematical physics, Indiana University.
95. Bradbury, K., Danziger, S., Smolensky, E., & Smolensky, P. (1979). Public assistance, female headship and economic well-being. Journal of Marriage and the Family, 519-535. [Reprinted in G. McDonald & F. Nye (Eds.), (1979), Family policy, National Council on Family Relations.]
96. Cicchetti, C., Gillen, W., & Smolensky, P. (1977). The Marginal Cost and Pricing of Electricity: An Applied Approach. Ballinger.

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Grants

• Smolensky, P., P.I.; Badecker, W., Brent, M., Burzio, L., Frank, R., Jusczyk, P., Legendre, G., Rapp, B., Vainikka, A. co-P.I.s. Problem-centered research training: Integrating formal and empirical methods in the cognitive science of language. Integrated Graduate Education and Research Training Program, NSF. 7/99-6/04
• Smolensky, P., P.I.; Brent, M., Brill, E., Frank, R., Jusczyk, P., Legendre, G., Prince, A., Stevenson, S., & Yarowsky, D., co-P.I.s. Optimization in language and language learning. Learning and Intelligent Systems Initiative, Knowledge Models and Cognitive Systems Program, NSF. 7/97-6/00.
• Smolensky, P., P.I.; Legendre, G., co-P.I. Integration of Connectionist and Symbolic Computation for Linguistic Modeling. Knowledge Models and Cognitive Systems Program, NSF. 1/93 - 6/96.
• Smolensky, P., P.I.; Legendre, G., co-P.I. Towards an Integrated Connectionist/Symbolic Theory of Higher Cognition. Linguistics Program, Human Cognition and Perception Program, and Cognitive Science Initiative, NSF. 8/92 - 7/94.
• Smolensky, P., P.I.; Legendre, G., co-P.I. Towards an Integrated Connectionist/Symbolic Theory of Higher Cognition: Research Experiences for Undergraduates Supplement. 1993.
• Mozer, M. C., P.I.; Smolensky, P., co-P.I. Connectionist Models Summer School. Cognitive Science Initiative and Knowledge Models and Cognitive Systems Program, NSF. 4/93 - 3/94.
• Prince, A., Smolensky, P., P.I.s. Universal phonology through harmony theory. Small Grant for Exploratory Research, Linguistics Program, NSF. 8/90 - 7/91.
• Smolensky, P., recipient. Gift for support development of the EUCLID system. Apple Computer, Inc. 9/90 - 9/91.
• Schnabel, R., P.I.; King, R., Lewis, C., Main, M., Nutt, G., Smolensky, P., co-P.I.s Effective use of parallel and distributed computing. Institutional Infrastructure Program, NSF. 9/90 - 8/95.
• Smolensky, P. P.I.; Fox, B., King, R., Lewis, C., co-P.I.s. Computer-aided reasoned discourse: the EUCLID system. Interactive Systems Program, Computer and Information Science and Engineering Directorate, NSF. 4/87 - 9/90.
• Smolensky, P. Investigator, Optical Connectionist Machine Program. NSF Engineering Research Center for Optoelectronic Computing Systems. 5/87 - 4/92.
• McNaughton, B., Nadel, L., O'Keefe, J., & Smolensky, P., co-P.I.s. Spatial computation in the mammalian hippocampal formation. Computational Neuroscience Program, Sloan Foundation. 2/87 - 2/90.
• Smolensky, P., P.I. Inference in massively parallel artificial intelligence systems. Information Science Program, Information Science and Technology Division, NSF. 8/86 - 7/89.
• Smolensky, P., P.I.; Anderson, D. Z., Cohen, M., Feinberg, J., co-P.I.s. Distributed processing in continuous optical media. Lightwave Technology Program, Engineering Division, NSF. 9/87 - 2/89.
• Smolensky, P., P.I. Support for research on connectionism and the EUCLID system. Symbolics, Inc. 9/86 - 8/89.

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Professional Activities

Invited Conference Presentations

• Annual Meeting of the Linguistic Society of America. San Francisco. January, 2002.
• Phonology Forum. Tokyo, Japan. August, 2001.
• International Cognitive Science Conference. Beijing, China. August, 2001.
• Presidential Address, Annual Meeting of the Society for Philosophy and Psychology. Cincinnati, OH. June, 2001.
• Optimality in Neural Networks and Grammar. International Conference on Cognitive and Neural Systems. Boston University, May, 2000.
• Recoverability and constraint interaction in phonology in syntax. Conference on the Optimization of Interpretation. Utrecht, The Netherlands, January, 2000.
• Overview of Optimality Theory. Symposium on Optimality Theory. Annual Conference of the Cognitive Science Society, Vancouver, August, 1999.
• Optimality in Neural Networks and Cognition. Workshop on Neuronal Assemblies, International Joint Conference on Neural Networks, Washington, D.C., July, 1999.
• Turbidity and opacity. Workshop on Phonology and the Lexicon. University of Alberta, Edmonton, June, 1999.
• Optimality and cognition. Inaugural Conference for the Program in Cognitive Science, University College Dublin, May, 1999.
• Phonological opacity and turbid representations in Optimality Theory. 35th Annual Meeting of the Chicago Linguistics Society, Chicago, April, 1999.
• Grammar and processing in OT syntax. Architectures and Mechanisms of Language Processing, Edinburgh, Scotland. September, 1997.
• Toward a generative theory of (OT) grammar use. Computational Psycholinguistics, Berkeley, CA. August, 1997.
• Universal Grammar and learnability in Optimality Theory. GALA Conference on Language Acquisition: Knowledge Representation and Processing, Edinburgh, Scotland. April, 1997.
• Controversies in cognitive science: The case of language. Invited Symposium Organizer/Moderator, Cognitive Science Society. San Diego. July, 1996.
• Connectionist generative linguistics, or, How and why I turned from radical-chic connectionism to embrace up-tight, east-coast, reactionary connectionism, or, In defense of constructive engagement in the politics of cognitive science. Invited symposium speaker: Celebration of the 10th anniversary of publication of the PDP books. Cognitive Science Society. San Diego. July, 1996.
• Putting classical computationalism in perspective. Speaker, discussant and organizer, symposium on Non-symbolic computation. Society for Philosophy and Psychology. San Francisco. June, 1996.
• Computational issues in Optimality Theory. Conference of the Computational Linguistics Special Interest Group of the German Linguistics Society. Düsseldorf, Germany. October, 1995.
• Current developments in Optimality Theory. Conference on Current Trends in Phonology: Models and Methods. Royaumont/Paris. July, 1995.
• When is less more? Faithfulness and minimal links in wh-chains. MIT Conference on Optimality in Syntactic Theory. Cambridge, MA. May, 1995.
• The adventures of John Locke in the Vapnik-Chervonenkis dimension, wherein he encounters Noam Chomsky. Annual Conference of the Cognitive Science Society. Atlanta, GA. August, 1994.
• Connectionism meets generative linguistics: Optimality in Universal Grammar. Plenary talk, First International Summer Institute in Cognitive Science. Buffalo, NY. July, 1994.
• Grammar as non-numerical optimization: Universal Grammar, learnability, and parsing in Optimality Theory. Annual Conference of the Association for Computational Linguistics, June, 1994.
• Optimality in language and cognition. Annual Conference of the Society for Philosophy and Psychology. Memphis, TN. June, 1994.
• Knowledge of language and its acquisition in Optimality Theory. Conference on Cognitive Models of Language Acquisition. Tilburg, The Netherlands. April, 1994.
• Optimality Theory: Universal grammar, connectionism, learnability and computability. CUNY Sentence Processing Conference. New York, NY. March, 1994.
• Harmony, markedness, and phonological activity. Keynote Address, Rutgers Optimality Workshop. New Brunswick, NJ. October, 1993.
• An integrated connectionist/symbolic theory of grammar. Annual Conference of the Cognitive Science Society. Boulder, CO. June, 1993. Integrated connectionist/symbolic computation and formal languages. International Symposia on Information Sciences. Fukuoka, Japan. July, 1992.
• Connectionism, compositionality, and the explanation of productivity. Conference on Cognition and Representation. Buffalo, NY. April, 1992.
• Optimality. Keynote address, West Coast Conference on Formal Linguistics XI. Los Angeles. February, 1992.
• Relating symbolic and sub?symbolic models of cognition: The High Road. Royal Society Conference on Hybrid Models of Cognition: The Problems of, and Requirements for, Combining the Use of Subsymbolic and Symbolic Computing. London. September, 1991.
• Harmonic Grammar: A connectionist approach to natural language syntax. Scandanavian Conference on Artificial Intelligence. Roskilde, Denmark. May, 1991.
• Connectionism and linguistic competence: Harmonic Grammar. CUNY Sentence Processing Conference. Rochester, NY. May, 1991.
• Optimality. Arizona Phonology Conference. Tucson, AZ. April, 1991.
• Neural and psychological interpretations of connectionist models. Neural networks, Harmony, and grammar. Symposium on Neural Networks. Linz, Austria. September, 1990.
• Parallel distributed processing of symbolic structure. Connectionism in Perspective. Zurich, Switzerland. October, 1988.
• Distributed representation of structured data. Neuro?Image. Bordeaux, France. October, 1988.
• Connectionism and psychological explanation: An honest assessment. Symposium on Connectionism and Psychological Explanation. National Meeting of the Society for Philosophy and Psychology. Chapel Hill, NC. May, 1988.
• Representing structured information in connectionist networks. Symposium on Parallel Distributed Processing in Man and Machine. European Meeting on Cybernetics and Systems Research. Vienna, Austria. April, 1988.
• Analyzing connectionist computation. Plenary address, Annual Meeting of the Society for Mathematical Psychology. Berkeley, CA. August, 1987.
• Computer-aided reasoned discourse. Panel on social science and system design: interdisciplinary collaborations. Human Factors in Computing Systems and Graphics Interfaces Conference. Toronto, Canada. April, 1987.
• At what level are the principles of cognition?-A connectionist position. Symposium on Connectionist Models and Neural Networks, National Meeting of the Society for Philosophy and Psychology. Baltimore, MD. June, 1986.
• Ethical questions and the military dominance in next-generation computing in America. Symposium on Ethical Issues in New Computing Technologies, National Conference of the Association for Computing Machinery. San Francisco, CA. October, 1984.

Invited Speaker Series Presentations

• Connectionist Universal Grammar. Ida Cordelia Beam Distinguished Lecture. University of Iowa. 1999.
• From Neurons to Universal Grammar. University of California at San Diego Cognitive Science Distinguished Speaker Series. 1996.
• Connectionism and Linguistics. Vassar College Cognitive Science Speaker Series. 1996.
• Connectionism and Universal Grammar. Cornell University. Cognitive Studies Speaker Series. 1995.
• Harmony?Theoretic Phonology. Rutgers University. Rutgers Center for Cognitive Science. December, 1992.
• Harmonic Grammar. University of Vienna. Artificial Intelligence and Cybernetics Speaker Series. September, 1990.
• From neurons to symbols: A multi-level framework for cognitive science. Memphis State University. University Lecture Series. January, 1990.
• Connectionism and cognitive architecture: An integrative approach. University of North Carolina, Chapel Hill. Program in Cognitive Science Speaker Series. January, 1990.
• Structuring knowledge in a neural net. Brandeis University, Center for Complex Cognitive, Neural, and Computational Systems. April, 1989.
• Language processing in connectionist networks: Some fundamental issues. Indiana University, Cognitive Science Speaker Series. April, 1989.
• Connectionist constituency: A reply to Fodor and Pylyshyn. MIT, Program in Cognitive Science. March, 1988. Vectorial representations and constituency in connectionist networks. University of Pennsylvania, Sloan Cognitive Science Series. January, 1988.
• Connectionism and levels of analysis in cognitive systems. University of Minnesota, New Directions in the Philosophy of Cognitive Science Series. May, 1987.
• On the proper treatment of connectionism. Princeton University, Program in Cognitive Science. February, 1987.
• The hypotheses underlying connectionism. University of California at Berkeley, Program in Cognitive Science. October, 1986.

Workshops Led

• Harmonic phonology. University of Arizona, Tucson, Cognitive Science Program. April, 1991.
• Connectionism and cognitive science. Vassar College, Poughkeepsie NY, Cognitive Science Program. May, 1991.

Invited Workshop Presentations

• Optimality Theory Workshop. Tokyo, Japan. August, 2001.
• Abstract genomic encoding of universal grammar in Optimality Theory. Workshop on Language and Evolution. Institute for Advanced Study. Princeton, NJ. May, 2001.
• Principles of Dave's Philosophy. Celebration honoring the career of David Rumelhart. Carnegie-Mellon University, October, 1999.
• Why syntax is different (but not really): Ineffability, violability and recoverability in syntax and phonology. Is syntax different? Common cognitive structure for syntax and phonology in Optimality Theory. Stanford. December, 1998.
• Constraint interaction in generative grammar II: Local Conjunction, or Random rules in Universal Grammar. Hopkins Optimality Theory Workshop/University of Maryland Mayfest. May, 1997.
• Tutorial: Optimality Theory (for syntacticians and others). Hopkins Optimality Theory Workshop/University of Maryland Mayfest. May, 1997.
• Generalizing optimization in OT: A competence theory of grammar 'use'. Workshop on Optimality Theory and Cognition. Stanford. December, 1996.
• Integrating connectionist and symbolic computation. NSF Conference on Approaches to AI. Santa Fe, NM. November, 1992.
• Compositionality, tensor product representations, and Harmonic Grammar. Interdisciplinary Workshop on Compositionality in Cognition and Neural Models. Paris. May, 1991.
• Harmonic Grammar. Language: With or without rules? Questions from universal grammar, cognitive grammar, and connectionism. Durham, New Hampshire. May, 1990.
• The connectionist view. Workshop on Iconic and Symbolic Representations in Mental Models. MIT. Cambridge, MA. March, 1990.
• Emergence of symbolic computation from connectionist computation. International Symposium on Synergetics of Cognition. Elmau, West Germany. June, 1989.
• On the relation between formal linguistics and connectionism. Workshop on Parallel Distributed Processing of Language. Vienna, Austria. April, 1988.
• The constituent structure of connectionist mental states. Spindel Philosophy Conference on Connectionism and the Philosophy of Mind. Memphis, TN. October, 1987.
• Cognitive modeling: relations between connectionist and symbolic approaches. Symposium on Cognitive Science. Cerisy-la-Salle, France. June, 1987.
• Analyzing connectionist computation. Symposium on Connectionism. University of Toronto, Canada. April, 1987.
• Computer-Aided Reasoned Discourse. Symposium on Cognitive Science: Theory, Methodology, and Applications, American Association for the Advancement of Science, Southwest and Rocky Mountain Division Annual Meeting. Boulder, CO. April, 1986.
• Cognition: From microstructure to macrostructure. Neural Connections/Mental Computation: Conference on Biological Computation. Tucson, AZ. February, 1986.
• Harmony theory and phase transitions in thermal models. Workshop on Parallel Distributed Processing. La Jolla, CA. June, 1984.
• A thermal model of problem solving. Workshop on Stochastic Parallel Computation. Boston, MA. May, 1984.

Contributed Conference Presentations

• Syntactic influences in relative clause attachment: An Optimality Theory account. CUNY Sentence Processing Conference. Philadelphia, PA. April, 2001.
• Phonological processing deficits in aphasia. Cognitive Science Society. Philadelphia, PA. August, 2000.
• Implementing the dual route in a single route. Cognitive Science Society. Vancouver. August, 1999.
• Optimality in sentence processing. Computational Psycholinguistics. Berkeley, CA. August, 1997.
• Optimal sentence processing. Hopkins Optimality Theory Workshop/University of Maryland Mayfest. May, 1997.
• The learnability of Optimality Theory. West Coast Conference on Formal Linguistics. San Diego, CA. February, 1994.
• Analytic typology of case marking and grammatical voice based on hierarchies of universal constraints. Berkeley Linguistics Society. Berkeley, CA. February, 1993.
• Harmonic Grammars for formal languages. Neural Information Processing Systems. Denver, CO. December, 1992.
• Harmonic Grammar: A progress report on connectionist mathematical linguistics. Third Conference on the Mathematics of Language. Austin, TX. November, 1992.
• Rule induction through integrated symbolic and subsymbolic processing. Neural Information Processing Systems. Denver, CO. December, 1991.
• The connectionist scientist game: Rule extraction and refinement in a neural network. Cognitive Science Society. Chicago, IL. July, 1991.
• Learning explicit rules in a neural network. International Joint Conference on Neural Networks. Seattle, WA. July, 1991.
• Unifying syntactic and semantic accounts of unaccusativity: A connectionist approach. Berkeley Linguistics Society. Berkeley, CA. February, 1991.
• Recursive structure processing and Harmonic Grammar. Neural Information Processing Systems. Denver, CO. November, 1990.
• Harmonic Grammar - A formal multi-level connectionist theory of linguistic well-formedness: An application. Cognitive Science Society. Cambridge, MA. July, 1990.
• Harmonic Grammar - A formal multi-level connectionist theory of linguistic well-formedness: Theoretical foundations. Cognitive Science Society. Cambridge, MA. July, 1990.
• Can connectionism contribute to syntax? Chicago Linguistics Society. Chicago, IL. April, 1990.
• Virtual memories and massive generalization in connectionist combinatorial learning. Cognitive Science Society. Ann Arbor, MI. August, 1989.
• Skeletonization: Trimming the fat from a network via relevance assessment. Neural Information Processing Systems. Denver, CO. November, 1988.
• Application of the interactive activation model to document retrieval. Neuro?Nîmes: Neural networks and their applications. Nîmes, France. November, 1988.
• Analyzing a connectionist model as a system of soft rules. Cognitive Science Society. Montreal, Canada. August, 1988.
• Analysis of distributed representation of constituent structure in connectionist systems. IEEE Conference on Neural Information Processing Systems: Natural and Synthetic. Denver, CO. November, 1987.
• On the connectionist reduction of conscious rule interpretation. Cognitive Science Society. Seattle, WA. July, 1987.
• Statistical mechanics and parallel computation. La Jolla Institute Center for Studies of Nonlinear Physics Dynamics Days. La Jolla, CA. January, 1985.
• Parallel computation: The brain and artificial intelligence. Southern California Artificial Intelligence Society. Los Angeles, CA. October, 1984.
• Formalizing task descriptions. International Federation for Information Processing Conference on Human-Computer Interaction. London, England. September, 1984.
• A parallel model of problem solving. Cognitive Science Society. Boulder, CO. June, 1984.
• The mathematical role of self?consistency in parallel computation. Cognitive Science Society. Boulder, CO. June, 1984.
• User-centered system documentation. Human Factors in Computer Systems. Boston, MA. December, 1983.
• Schema selection and stochastic inference in modular environments. National Conference on Artificial Intelligence. Washington, DC. August, 1983.
• Cognitive temperature and learning in connectionist models. Cognitive Science Society. Rochester, NY. May, 1983.

Colloquium and Seminar Presentations (since 1995)

2001

• Brain and Cognitive Science Colloquium, Rochester University
• Linguistics Colloquium, SUNY Stony Brook

2000

• Linguistics Colloquium, University of California, Los Angeles

1999

• Linguistics Colloquium, University of Massachusetts at Amherst
• Physics Colloquium, Rutgers University

1998

• Cognitive Science Round Table, Stanford University.
• Linguistics Colloquium, Stanford University. Linguistics Colloquium, NYU.
• Linguistics Colloquium, Yale University.
• Applied Physics Laboratory Colloquium, Johns Hopkins University.
• Philosophy Colloquium, Johns Hopkins University.

1997

• Center for Cognitive Science Colloquium, Rutgers University.
• Optimality Theory Research Seminar, Rutgers University.

1996

• Linguistics Colloquium, Stanford University.
• Language Acquisition Seminar, Stanford University.

1995

• Computer Science Colloquium, Rutgers University.
• Linguistics Colloquium, Cornell University.
• Program in Cognitive Science and Linguistics Colloquium, MIT.
• Linguistics Colloquium, University of Southern California.
• Linguistics Colloquium, University of Maryland.
• Institute for Research in Cognitive Science Colloquium, University of Pennsylvania.
• Linguistics Colloquium, University of California, Los Angeles.
• Linguistics Colloquium, University of Delaware.

Service to National Scientific Organizations

• National Academy of Sciences/Institute of Medicine Workshop, Opportunities for Interdisciplinary Training, Invited Speaker, 1999.
• NSF Science and Technology Center Program site visit team member, 1996.
• NSF Workshop on Learning and Intelligent Systems Initiative Team Leader, 1995.
• NSF Young Investigator Award Panel, 1993.
• NSF Workshop on Approaches to AI, 1993 NSF Cognitive Science Initiative Workshop, 1991.
• NSF Science and Technology Center Program panel member and site visit team chairman, 1990.
• NSF Institutional Infrastructure Program site visit team member, 1989.
• NSF Workshop on Connectionism and Cognitive Science, 1986.

Professional Societies

• Cognitive Science Society
• Linguistics Society of America
• Society for Philosophy and Psychology
• Institute of Electrical and Electronics Engineers, Special Interest Group on Neural Networks
• International Neural Networks Society
• Computer Professionals for Social Responsibility

University Service

• Brain and Behavioral Sciences Advisory Committee
• Krieger-Eisenhower Chair Selection Committee
• Anthropology Department Senior Search Committee
• Undergraduate Writing Requirement Evaluation Committee
• Ad hoc promotion/appointment committees: Computer Science, Anthropology, Psychology

Courses Developed

• Formal methods in cognitive science: neural networks. Fall 1998.
• Graduate phonology II. Spring 1997.
• Graduate phonology I. Fall 1996.
• Minds, brains, and computers. Spring 1996.
• Seminar in Optimality Theoretic phonology. Spring 1995.
• Seminar in Optimality Theory and connectionism in linguistics. Spring 1994.
• Computation for cognitive scientists (for non?computer?science graduate students). Spring 1993.
• Mathematical perspectives on neural networks. Spring 1991.
• Modules for Introduction to AI: Logic; Cognitive Modeling; Machine Learning. Fall 1990.
• Foundations of cognitive science. Fall 1989.
• Advanced seminar in connectionist modeling. Spring 1988.
• Topics in cognitive science: Connectionism; Formal Syntax. Spring 1988.
• Survey of cognitive science. Fall 1987.
• Introduction to connectionist AI. Spring 1986.
• Advanced AI programming. Fall 1985.

Doctoral Thesis Supervision

• Hale, John. Optimality-Theoretic Syntax in Neural Networks. Department of Cognitive Science, Johns Hopkins University. Expected completion, 2003.
• Davidson, Lisa. Second-Language Phonology Acquisition. Department of Cognitive Science, Johns Hopkins University. Expected completion, 2003.
• Goldrick, Matthew. Phonological Processing and Aphasia. Department of Cognitive Science, Johns Hopkins University. Expected completion, 2002.
• Gafos, Diamandis. The Articulatory Basis of Locality in Phonology. Department of Cognitive Science, Johns Hopkins University. 1996.
• Tesar, Bruce. Computational Optimality Theory. Department of Computer Science, University of Colorado. 1995.
• Lynn, Patrick. System Interaction in Human Memory and Amnesia: Theoretical Analysis and Connectionist Modeling. Department of Computer Science, University of Colorado. 1994.
• Bernstein, Bernard. EUCLID Supports Informal Argumentation with Hypertext. Department of Computer Science, University of Colorado. 1993.
• McMillan, Clayton. (Co-supervisor with Michael Mozer) Rule Induction in a Neural Network through Symbolically Constrained Subsymbolic Processing. Department of Computer Science, University of Colorado. 1992.
• Brousse, Olivier. Systematicity and Generativity in Neural Network Combinatorial Learning. Department of Computer Science, University of Colorado. 1991.
• Sanger, Dennis. Contribution Analysis: A Technique for Assigning Responsibilities to Hidden Units in Connectionist Networks. Department of Computer Science, University of Colorado. 1990.

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Contact Information

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