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Tesar, Bruce & Smolensky, Paul (1995). The Learnability of Optimality Theory: An Algorithm and Some Basic Complexity Results.

*The learnability of optimality theory: an algorithm and some basic complexity results.* Retrieved from

http://dx.doi.org/doi:10.7282/T34Q7SB7
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**The Learnability of Optimality Theory: An Algorithm and Some Basic Complexity Results** (1995)

Bruce Tesar, Paul Smolensky

The learnability of optimality theory: an algorithm and some basic complexity results..

AbstractIf Optimality Theory (Prince & Smolensky 1991, 1993) is correct, Universal Grammar provides a set of universal constraints which are highly general, inherently conflicting, and consequently rampantly violated in the surface forms of languages. A languageās grammar ranks the universal constraints in a dominance hierarchy, higher-ranked constraints taking absolute priority over lower-ranked constraints, so that violations of a constraint occur in well-formed structures when, and only when, they are necessary to prevent violation of higher-ranked constraints. Languages differ principally in how they rank the universal constraints in their language-specific dominance hierarchies. The surface forms of a given language are structural descriptions of inputs which are optimal in the following sense: they satisfy the universal constraints, or, when these constraints are brought into conflict by an input, they satisfy the highest-ranked constraints possible. This notion of optimality is partly language-specific, since the ranking of constraints is language-particular, and partly universal, since the constraints which evaluate well-formedness are (at least to a considerable extent) universal. In many respects, ranking of universal constraints in Optimality Theory plays a role analogous to parameter-setting in principles-and-parameters theory.

SubjectsLearnability, RCD algorithm, Recursive Constraint Demotion, Learning problem, Harmonic ordering, Grammar, Comparative and general--Word order

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