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- Adam Jardine
- 2013

The current study examines the generative power of Autosegmental Phonology (Goldsmith, 1976, 1979, 1990) in the framework of Formal Language Theory, with which we can study the computational complexity of phonological phenomena and formalisms independent of specific theoretical frameworks in phonology. A methodology for a model-theoretic study of… (More)

- Adam Jardine, Jeffrey Heinz
- TACL
- 2016

The Tier-based Strictly 2-Local (TSL2) languages are a class of formal languages which have been shown to model long-distance phonotactic generalizations in natural language (Heinz et al., 2011). This paper introduces the Tier-based Strictly 2-Local Inference Algorithm (2TSLIA), the first nonenumerative learner for the TSL2 languages. We prove the 2TSLIA is… (More)

In this work, we consider an agent playing a turnbased game in a known environment against an adversary with unknown dynamics. The model of the adversary is assumed to belong to a subclass of regular languages that can be learned in the limit. We use tools from formal methods to synthesize a control strategy for the agent to win the game as it learns the… (More)

- Adam Jardine, Jane Chandlee, Rémi Eyraud, Jeffrey Heinz
- ICGI
- 2014

In this paper, we present a new algorithm that can identify in polynomial time and data using positive examples any class of subsequential functions that share a particular finitestate structure. While this structure is given to the learner a priori, it allows for the exact learning of partial functions, and both the time and data complexity of the… (More)

- Adam Jardine, Jeffrey Heinz
- MOL
- 2015

Autosegmental phonology represents words with graph structures. This paper introduces a way of reasoning about autosegmental graphs as strings of concatenated graph primitives. The main result shows that the sets of autosegmental graphs so generated obey two important, putatively universal, constraints in phonological theory provided that the graph… (More)

- Adam Jardine
- 2015

Long-distance phonotactics, in which the surface sounds of a language are subject to coocurrence constraints referring to nonadjacent segments, present a difficult learning problem. To acquire such patterns, a learner must find dependencies among distant segments. This paper approaches an idealized version of this problem: how can these patterns even be… (More)

The current study identifies locality as a near-universal property of phonological input-output mappings that describe processes with local triggers and presents a learning algorithm which uses locality as an inductive principle to generalize such mappings from finite data. Input-output (or UR-SR) mappings like the one in (1) are integral to both the… (More)

- Adam Jardine, Kevin McMullin
- LATA
- 2017

We introduce the Tier-based k-Strictly Local Inference Algorithm (kTSLIA), an algorithm that learns the class of Tier-based Strictly k-Local (TSLk) formal languages in polynomial time on a sample of positive data whose size is bounded by a constant. The TSLk languages are useful in modeling the cognition of sound patterns in natural language [6, 11], and it… (More)

- Prasanna Kannappan, Konstantinos Karydis, Herbert G. Tanner, Adam Jardine, Jeffrey Heinz
- 2016 24th Mediterranean Conference on Control and…
- 2016

The paper demonstrates that aspects of resilience of supervisory Cyber-Physical Systems (CPSs) can be improved through the inclusion of appropriate learning modules in the subordinate autonomous agents. During normal operation, individual agents keep track of their supervisor's commands and utilize the learning module, based on Grammatical Inference, to… (More)

This paper presents an algorithm which learns phonological grammars. These phonological grammars— like grammars in Optimality Theory (OT, Prince & Smolensky, 2004) or rule-based grammars (Chomsky & Halle, 1968)—describe phonological maps, or the transformations from input (underlying) forms to output (surface) forms (Tesar, 2014). Like OT grammars, the… (More)