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The Learnability of Optimality Theory: An Algorithm and Some Basic Complexity Results
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The Learnability of Optimality Theory: An Algorithm and Some Basic Complexity Results

Bruce Tesar and Paul Smolensky
The learnability of optimality theory: an algorithm and some basic complexity results.
Johns Hopkins University, Department of Computer Science
1995
DOI:
https://doi.org/10.7282/T34Q7SB7

Abstract

Learnability RCD algorithm Recursive Constraint Demotion Learning problem Harmonic ordering Grammar, Comparative and general--Word order
If 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 language’s 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.
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