Primary Area: Universal grammar -- Optimality Theory: phonology, syntax, acquisition, learnability, processing.
Secondary Areas: Integration of connectionist ('neural') and symbolic computation: computational, linguistic, and philosophical issues. Precise theories of higher cognitive domains like language and reasoning 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 intelligence resides in the brain, where computation appears to be numerical, not symbolic; parallel, not serial; quite distributed, not as highly localized as in symbolic systems. Furthermore, when observed carefully, much of human behavior is remarkably sensitive to the detailed statistical properties of experience; hard-edged rule systems seem ill-equipped to handle these subtleties. My research attempts to identify the proper roles within a unified theory of cognition for symbolic computation, numerical neural computation, and statistical computation. More specifically, the basic questions driving this research include: What are the central general principles of computation in connectionist -- abstract neural -- networks? How can these principles be reconciled with those of symbolic computation? Addressing these questions over the past two decades, my 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? The connectionist conception of intuitive knowledge as a collection of conflicting soft constraints, interacting via optimization of well-formedness or Harmony, led in joint research with Géraldine Legendre to the connectionist-based formalism of Harmonic Grammar. Incorporating the richly structured representations and universal well-formedness constraints of symbolic linguistic theory, Alan Prince and I developed a grammar formalism called Optimality Theory which brings general connectionist computational principles of optimization into the heart of the symbolic theory of universal grammar. The optimization that emerges is no longer inherently numerical: 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 (OT), possible human languages share a common set of universal constraints on well-formedness. These constraints are highly general, and hence conflict; thus 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 fixed set of 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 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.
(since 1995) |
| | Michael Oliver | Ph.D. student, Cognitive Science, JHU | Connectionism and the foundations of cognitive science | | Oren Schwartz | Ph.D. student, Cognitive Science, JHU | Computational modeling of human speech perception | | Rebecca Morley | Postdoc, Linguistics, Ohio State | Generalization, Lexical Statistics, and Typologically Rare Systems. 2008 | | Sara Finley | Postdoc, Brain & Cognitive Sciences, Rochester | Formal and Cognitive Restrictions on Vowel Harmony. 2008 | | Gaja Jarosz | Assistant Professor of Linguistics, Yale | Rich Lexicons and Restrictive Grammars – Maximum Likelihood Learning in Optimality Theory. 2006 | Adam Buchwald
(Co-advisor: B. Rapp)
| Assistant Professor of Speech-Language Pathology and Audiology, NYU | Sound structure representation, repair and well-formedness: Grammar in spoken language production. 2005 | | Lisa Davidson | Assistant Professor of Linguistics,
NYU | The atoms of phonological representation: Gestures, coordination and perceptual features in consonant cluster phonotactics. 2003 | | John Hale | Associate Professor of Linguistics,
Cornell | Grammar, uncertainty, and sentence processing. 2003 | | Bruce Tesar | Associate Professor of Linguistics,
Rutgers | Computational Optimality Theory. 1995. Computer Science, U. of Colorado
| | Rebecca Piorkowski
(Primary: W. Badecker) | | Auditory Language Processing.
Processing Grammatical Agreement. | Tamara Nicol
(Primary: B. Landau) | Postdoc, IRCS, U. Penn | Learning which verbs allow object omission: Verb semantic selectivity and the implicit object construction. 2007 | Matt Goldrick
(Primary: B. Rapp) | Assistant Professor of Linguistics,
Northwestern | Patterns in sound, patterns in mind: Phonological regularities in speech production. 2002 | Colin Wilson
(Primary: L. Burzio) | Assistant Professor of Cognitive Science,
Johns Hopkins | Targeted Constraints: An Approach to Positional Neutralization in Optimality Theory. 2000 | Adamantios Gafos
(Primary: L. Burzio) | Associate Professor of Linguistics,
NYU | The Articulatory Basis of Locality in Phonology. 1996 |
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.
- Krieger-Eisenhower Professor of Cognitive Science, Johns Hopkins University, 2006-present.
- Full Professor, Department of Cognitive Science, Johns Hopkins University, 1994-present.
- Chair, Department of Cognitive Science, Johns Hopkins University, Jan. 1997 - June 1998 (Acting), July 1998 - June 2000.
- Adjunct Professor, Department of Linguistics, University of Maryland at College Park, 1994-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, International Summer School in Cognitive Science, New Bulgarian University, Sofia, 2008
- Faculty, Linguistic Institute, MIT/Harvard, 2005.
- 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.
- National Science Foundation, John H. Edwards, and Indiana University Graduate Fellow, 1976-81.
Chaire Internationale de Recherche Blaise Pascal, 2008 David E. Rumelhart Prize for Theoretical Contributions to Cognitive Science, 2005 Teaching Award Nomination, for ‘Minds, Brains and Computers,’ Cognitive Science 109, and ‘Advanced Topics in Sound Structure,’ 1998 Guggenheim Foundation Fellowship, 1995–96. President, Society for Philosophy and Psychology. 2000 – 01. President, Cognitive Science Society. 1995 – 96, 1996 – 97. 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.
- Presentation sections
o Paris lectures, May 2005 (Département d’Etudes Cognitives, Ecole Normale Supérieure)
1. Optimization and symbols in neural networks [2.3M]
2. Optimization in grammar [10M]
o OT & Markedess Theory (8 slides).ppt [76K]
o BrbrNet (12 slides).ppt (Local connectionist implementation of a Harmonic Grammar for syllabification in Berber) [3.5M]
o Lango ATR Harmony (17 slides).ppt [.6M]
o SHarC Theorem (5 slides).ppt [92K]
o Infant NPA Experiments (8 + 4 slides).ppt [151K]
o The Priority of Markedness (32 slides).ppt [244K]
o ICS Architecture (25 slides).ppt [2.7M]
o HG Parser (10 slides).ppt [2M]
o CVNet (18 slides).ppt [182K]
o Harmonic Mind Wrappers.ppt [41K]
o CVNet (1 slide).ppt [57K]
o Learnability in OT (3 slides).ppt [54K]
o Intro to OT (6 slides).ppt [127K] - An Integrated Connectionist/Symbolic (ICS) Cognitive Architecture. Seoul National University. November, 2002. [4.4M ppt file]
- Jakobson's Grand Unified Theory of Linguistic Cognition. Seoul National University. November, 2002. [.5M ppt file]
- Constraint Conjunction and Strong Harmonic Completeness. Korean Phonological Society. November, 2002.[0.6M ppt file]
- The Harmonic Mind. Cognition Workshop. North American Summer School for Logic, Language, and Information. Stanford University. July, 2002. [2.4M ppt file]
- Markedness Optimization in Grammar and Cognition. Plenary Lecture, Annual Meeting of the Linguistic Society of America. San Francisco. January, 2002. [1M ppt file]
- Formal Typology: Explanation in Optimality Theory. Phonology Forum. Tokyo, Japan. August, 2001. [0.5M ppt file]
- The Harmonic Mind. International Cognitive Science Conference. Beijing, China. August, 2001. [2M ppt file]
- The Harmonic Mind. Presidential Address, Annual Meeting of the Society for Philosophy and Psychology. Cincinnati, OH. June, 2001. [4M ppt file]
ROA = http://roa.rutgers.edu/, the Rutgers Optimality Archive
- Smolensky, Paul & Legendre, Géraldine. 2006. The Harmonic Mind: From Neural Computation To Optimality-Theoretic Grammar Vol. 1: Cognitive Architecture; vol. 2: Linguistic and Philosophical Implications. MIT Press.
 - Prince, Alan & Smolensky, Paul. 2004. Optimality Theory: Constraint interaction in generative grammar. Blackwell. as 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 1993. Rutgers Optimality Archive 537 version, 2002.
 - Tesar, Bruce & Smolensky, Paul. 2000. Learnability in Optimality Theory. MIT Press.
 - Smolensky, Paul, Mozer, Michael C., & Rumelhart, David E. (eds.). 1996. Mathematical perspectives on neural networks. Erlbaum.
- Berent, I., Lennertz, T., Smolensky, P. & Vaknin, V. To appear. Speakers’ knowledge of phonological universals: Evidence from nasal clusters. Phonology.
- Berent, I., Lennertz, T., Jun, J., Moreno, M. A. & Smolensky, P. 2008. Language universals in human brains. Proceedings of the National Academy of Sciences USA 105, 5321–5.
- Smolensky, P. 2006. Harmony in linguistic cognition. Cognitive Science 30, 779–801.
- Smolensky, P. 2006. On theoretical facts and empirical abstractions. In E. Bakovic, J. Ito, and J. McCarthy (eds.), Wondering at the Natural Fecundity of Things: Essays in Honor of Alan Prince. Santa Cruz, CA: Linguistics Research Center [http://repositories.cdlib.org/lrc/prince/13].
- Hagstrom P., Chen-Main, J., Legendre, G., Tao, L. & Smolensky, P. 2004. Deriving output probabilities in Child Mandarin from a Dual-Optimization grammar. Lingua. 114, 1147–85.
- Smolensky, P. 2003. Markedness, Harmony, and phonological invisibility. Journal of Cognitive Science. 4, 1–41.
- Jusczyk, P. W., Smolensky, P., and Allocco, T. 2002. How English-learning infants respond to markedness and faithfulness constraints. Language Acquisition 10, 31–73.
- Smolensky, P. 1999. Grammar-based connectionist approaches to language. Cognitive Science. 23, 589-613.
- Tesar, B. & Smolensky, P. 1998. Learnability in Optimality Theory. Linguistic Inquiry, 29, 229-68
- Prince, A. & Smolensky, P. 1997. Optimality: From neural networks to universal grammar. Science 275, 1604–10.
- Smolensky, P. 1996. On the comprehension/production dilemma in child language. Linguistic Inquiry 27, 720–31.
- Smolensky, P. 1990. Tensor product variable binding and the representation of symbolic structures in connectionist networks. Artificial Intelligence, 46, 159–216.
- Smolensky, P. 1990. In defense of PTC: Reply to continuing commentary. The Behavioral and Brain Sciences. 13, 407–11.
- Mozer, M. C., & Smolensky, P. 1989. Using relevance to reduce network size automatically. Connection Science, 1, 3–16.
- Dolan, C. & Smolensky, P. 1989. Tensor Product Production System: A modular architecture and representation. Connection Science, 1, 53–68.
- Smolensky, P. 1988. Putting Together Connectionism—again. The Behavioral and Brain Sciences, 11, 59–74.
- Smolensky, P. 1988. On the proper treatment of connectionism. The Behavioral and Brain Sciences, 11, 1–23.
- Smolensky, P. 1987. The constituent structure of connectionist mental states: A reply to Fodor and Pylyshyn. Southern Journal of Philosophy, 26 (Supplement), 137–63.
- Smolensky, P. 1987. Connectionist AI, symbolic AI, and the brain. Artificial Intelligence Review, 1, 95–109.
- 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.
- 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.
- 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.
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