Improving the Tractable Lexicon Size for the Rational Speech Act Model

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dc.contributor.advisorBraak, van de, L.D.
dc.contributor.advisorRooij, van, I.J.E.I.
dc.contributor.authorHilbrands, Jelle Philip
dc.date.issued2021-06-21
dc.description.abstractThe Rational Speech Act model adapted to resolving misunderstandings in conversation is conjectured to be intractable. A combinatorial explosion in searching through the space of possible lexicons is likely responsible for this intractability. Coming from a xed-parameter tractability view, where intractable problems can become tractable for restricted input parameters, I have introduced and tested two constraints on possible lexicons in an attempt to improve upon the feasibly computable lexicon size. Stemming from an intuition that humans use these constraints as well, one constraint is the use of knowledge or facts for generating lexicons. Some words can have very speci c and unambiguous meanings. The other constraint is about the use of similarity or neighborliness to generate new lexicons. The other person will likely have a similar meaning for the same word. I named these constraints factual lexicons and neighboring lexicons. The former is formalized as xing a certain amount of mappings of signal and referent that are always existent. The latter is formalized as considering similar lexicons as compared to the current one available to the agent. Both constraints were formalized in the Human Language Constrained Rational Speech Act model. The results indicate that factual lexicons improve to a lesser extent the time and space performance of the model and result in degraded model accuracy when resolving misunderstandings. Neighboring lexicons improve to a much larger extent time and space performance and also improve upon accuracy. As of writing, both the intractability of the problem and the xed-parameter tractability approach are unproven. Nevertheless, these results hint at the capability of constraints to improve upon the feasibly computable lexicon size for the RSA model. However, I am not convinced that the constraints are a xed-parameter solution to an unproven problem.
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/15706
dc.language.isoen
dc.thesis.facultyFaculteit der Sociale Wetenschappen
dc.thesis.specialisationspecialisations::Faculteit der Sociale Wetenschappen::Artificial Intelligence::Bachelor Artificial Intelligence
dc.thesis.studyprogrammestudyprogrammes::Faculteit der Sociale Wetenschappen::Artificial Intelligence
dc.thesis.typeBachelor
dc.titleImproving the Tractable Lexicon Size for the Rational Speech Act Model
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