Universal Generation for Optimality Theory Is PSPACE-Complete

Author:

Hao Sophie1

Affiliation:

1. New York University, Center for Data Science. sophie.hao@nyu.edu

Abstract

Abstract This article shows that the universal generation problem for Optimality Theory (OT) is PSPACE-complete. While prior work has shown that universal generation is at least NP-hard and at most EXPSPACE-hard, our results place universal generation in between those two classes, assuming that NP ≠ PSPACE. We additionally show that when the number of constraints is bounded in advance, universal generation is at least NL-hard and at most NPNP-hard. Our proofs rely on a close connection between OT and the intersection non-emptiness problem for finite automata, which is PSPACE-complete in general and NL-complete when the number of automata is bounded. Our analysis shows that constraint interaction is the main contributor to the complexity of OT: The ability to factor transformations into simple, interacting constraints allows OT to furnish compact descriptions of intricate phonological phenomena.

Publisher

MIT Press

Subject

Artificial Intelligence,Computer Science Applications,Linguistics and Language,Language and Linguistics

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