|Residence United States|
Fields Cognitive science
Name Paul Smolensky
|Born May 5, 1955 (age 60) (1955-05-05) |
Institutions The Johns Hopkins University
Alma mater Harvard University, Indiana University
Known for Optimality theory, phonology, syntax, acquisition, learnability, processing, restricted Boltzmann machines
Education Indiana University Bloomington (1981), Harvard University (1976)
Awards Rumelhart Prize, Guggenheim Fellowship for Social Sciences, US & Canada
Books Optimality Theory: Constrain, Learnability in Optimality, The harmonic mind, Developments in Connecti
Notable awards Rumelhart Prize (2005)
Dcs paul smolensky integrating connectionist and symbolic computation in grammatical theory
Paul Smolensky (born May 5, 1955) is a professor of Cognitive Science at the Johns Hopkins University.
- Dcs paul smolensky integrating connectionist and symbolic computation in grammatical theory
- Paul smolensky uc merced mts talk series fall 2015
Along with Alan Prince, he developed Optimality Theory, a representational model of linguistics. Optimality Theory is popularly used for phonology, the subfield to which it was originally applied, but has been extended to other areas of linguistics such as syntax and semantics.
Smolensky is the recipient of the 2005 Rumelhart Prize for his pursuit of the ICS Architecture, a model of cognition that aims to unify Connectionism and symbolism, where the symbolic representations and operations are manifested as abstractions on the underlying connectionist networks. Among his other important ideas is the notion of local conjunction of constraints - the idea that two constraints can combine into a single constraint that is violated only when both of its conjuncts are violated. Local conjunction has been applied to the analysis of various "super-additive" effects in Optimality Theory. With Bruce Tesar (Rutgers University), Smolensky has also contributed significantly to the study of the learnability of Optimality Theoretic grammars.
He is a member of the Center for Language and Speech Processing.