Results for 'Learnability problem'

977 found
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  1.  39
    Empiricism and Language Learnability.Nick Chater, Alexander Simon Clark, John A. Goldsmith & Amy Perfors - 2015 - Oxford University Press UK.
    This interdisciplinary new work explores one of the central theoretical problems in linguistics: learnability. The authors, from different backgrounds---linguistics, philosophy, computer science, psychology and cognitive science-explore the idea that language acquisition proceeds through general purpose learning mechanisms, an approach that is broadly empiricist both methodologically and psychologically. Written by four researchers in the full range of relevant fields: linguistics, psychology, computer science, and cognitive science, the book sheds light on the central problems of learnability and language, and traces (...)
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  2.  32
    On characterizations of learnability with computable learners.Tom F. Sterkenburg - 2022 - Proceedings of Machine Learning Research 178:3365-3379.
    We study computable PAC (CPAC) learning as introduced by Agarwal et al. (2020). First, we consider the main open question of finding characterizations of proper and improper CPAC learning. We give a characterization of a closely related notion of strong CPAC learning, and provide a negative answer to the COLT open problem posed by Agarwal et al. (2021) whether all decidably representable VC classes are improperly CPAC learnable. Second, we consider undecidability of (computable) PAC learnability. We give a (...)
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  3.  18
    Embedded feature selection for neural networks via learnable drop layer.M. J. JimÉnez-Navarro, M. MartÍnez-Ballesteros, I. S. Brito, F. MartÍnez-Álvarez & G. Asencio-CortÉs - forthcoming - Logic Journal of the IGPL.
    Feature selection is a widely studied technique whose goal is to reduce the dimensionality of the problem by removing irrelevant features. It has multiple benefits, such as improved efficacy, efficiency and interpretability of almost any type of machine learning model. Feature selection techniques may be divided into three main categories, depending on the process used to remove the features known as Filter, Wrapper and Embedded. Embedded methods are usually the preferred feature selection method that efficiently obtains a selection of (...)
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  4.  48
    Model-based learning problem taxonomies.Richard M. Golden - 1997 - Behavioral and Brain Sciences 20 (1):73-74.
    A fundamental problem with the Clark & Thornton definition of a type-1 problem (requirement 2) is identified. An alternative classical statistical formulation is proposed where a type-1 (learnable) problem corresponds to the case where the learning machine is capable of representing its statistical environment.
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  5.  23
    The puzzle of ideography.Olivier Morin - 2023 - Behavioral and Brain Sciences 46:e233.
    An ideography is a general-purpose code made of pictures that do not encode language, which can be used autonomously – not just as a mnemonic prop – to encode information on a broad range of topics. Why are viable ideographies so hard to find? I contend that self-sufficient graphic codes need to be narrowly specialized. Writing systems are only an apparent exception: At their core, they are notations of a spoken language. Even if they also encode nonlinguistic information, they are (...)
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  6. Epistemic Limitations and Precise Estimates in Analog Magnitude Representation.Justin Halberda - 2016 - In A. Baron & D. Barner, Core Knowledge and Conceptual Change. Oxford University Press. pp. 167-186.
    This chapter presents a re-understanding of the contents of our analog magnitude representations (e.g., approximate duration, distance, number). The approximate number system (ANS) is considered, which supports numerical representations that are widely described as fuzzy, noisy, and limited in their representational power. The contention is made that these characterizations are largely based on misunderstandings—that what has been called “noise” and “fuzziness” is actually an important epistemic signal of confidence in one’s estimate of the value. Rather than the ANS having noisy (...)
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  7.  2
    Many problems, different frameworks: classification of problems in computable analysis and algorithmic learning theory.Vittorio Cipriani - 2024 - Bulletin of Symbolic Logic 30 (2):287-288.
    In this thesis, we study the complexity of some mathematical problems: in particular, those arising in computable analysis and algorithmic learning theory for algebraic structures. Our study is not limited to these two areas: indeed, in both cases, the results we obtain are tightly connected to ideas and tools coming from different areas of mathematical logic, including for example descriptive set theory and reverse mathematics.After giving the necessary preliminaries, we first study the uniform computational strength of the Cantor–Bendixson theorem in (...)
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  8. The neural basis of cognitive development: A constructivist manifesto.Steven R. Quartz & Terrence J. Sejnowski - 1997 - Behavioral and Brain Sciences 20 (4):537-556.
    How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with recent neurobiological evidence (...)
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  9.  91
    The Logical Problem of Language Acquisition: A Probabilistic Perspective.Anne S. Hsu & Nick Chater - 2010 - Cognitive Science 34 (6):972-1016.
    Natural language is full of patterns that appear to fit with general linguistic rules but are ungrammatical. There has been much debate over how children acquire these “linguistic restrictions,” and whether innate language knowledge is needed. Recently, it has been shown that restrictions in language can be learned asymptotically via probabilistic inference using the minimum description length (MDL) principle. Here, we extend the MDL approach to give a simple and practical methodology for estimating how much linguistic data are required to (...)
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  10. Why and how the problem of the evolution of universal grammar (UG) is hard.Stevan Harnad - 2008 - Behavioral and Brain Sciences 31 (5):524-525.
    Christiansen & Chater (C&C) suggest that language is an organism, like us, and that our brains were not selected for Universal Grammar (UG) capacity; rather, languages were selected for learnability with minimal trial-and-error experience by our brains. This explanation is circular: Where did our brain's selective capacity to learn all and only UG-compliant languages come from?
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  11.  16
    One Cue's Loss Is Another Cue's Gain—Learning Morphophonology Through Unlearning.Erdin Mujezinović, Vsevolod Kapatsinski & Ruben van de Vijver - 2024 - Cognitive Science 48 (5):e13450.
    A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney, Kügler, & van de Vijver, 2015; Baer-Henney & van de Vijver, 2012), error-driven learning suggests that contingency rather than contiguity is crucial (Nixon, 2020; Ramscar, Yarlett, Dye, (...)
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  12. Moorean Phenomena in Epistemic Logic.Wesley H. Holliday & Thomas F. Icard - 2010 - In Lev Dmitrievich Beklemishev, Valentin Goranko & Valentin Shehtman, Advances in Modal Logic 8. London, England: College Publications. pp. 178-199.
    A well-known open problem in epistemic logic is to give a syntactic characterization of the successful formulas. Semantically, a formula is successful if and only if for any pointed model where it is true, it remains true after deleting all points where the formula was false. The classic example of a formula that is not successful in this sense is the “Moore sentence” p ∧ ¬BOXp, read as “p is true but you do not know p.” Not only is (...)
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  13.  10
    Moorean Phenomena in Epistemic Logic.Wesley H. Holliday & Thomas F. Icard Iii - 1998 - In Marcus Kracht, Maarten de Rijke, Heinrich Wansing & Michael Zakharyaschev, Advances in Modal Logic. CSLI Publications. pp. 178-199.
    A well-known open problem in epistemic logic is to give a syntactic characterization of the successful formulas. Semantically, a formula is successful if and only if for any pointed model where it is true, it remains true after deleting all points where the formula was false. The classic example of a formula that is not successful in this sense is the “Moore sentence” p ∧ ¬ BOX p, read as “p is true but you do not know p.” Not (...)
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  14.  24
    Moorean Phenomena in Epistemic Logic.Wesley H. Holliday & Thomas F. Icard Iii - 1998 - In Marcus Kracht, Maarten de Rijke, Heinrich Wansing & Michael Zakharyaschev, Advances in Modal Logic. CSLI Publications. pp. 178-199.
    A well-known open problem in epistemic logic is to give a syntactic characterization of the successful formulas. Semantically, a formula is successful if and only if for any pointed model where it is true, it remains true after deleting all points where the formula was false. The classic example of a formula that is not successful in this sense is the “Moore sentence” p ∧ ¬ BOX p, read as “p is true but you do not know p.” Not (...)
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  15.  24
    Pragmatic interpretation and the production of ideographic codes.Leda Berio, Berke Can, Katharina Helming, Giulia Palazzolo & Richard Moore - 2023 - Behavioral and Brain Sciences 46:e236.
    We argue that the problem of ideographic codes stems from neither learnability nor standardization, but from a general issue of pragmatic interpretation. As ideographic codes increase in expressive power, in order to reduce ambiguity, they must become more detailed – such that production becomes more cumbersome, and requires greater artistry on the part of users, limiting their capacity for growth.
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  16.  16
    In Critical Condition: Polemical Essays on Cognitive Science and the Philosophy of Mind.Jerry A. Fodor - 1998 - MIT Press.
    PREFACE PART I METAPHYSICS Review of John McDowell’s Mind and World Special Sciences: Still Autonomous after All These Years Conclusion Acknowledgment Notes PART II CONCEPTS Review of Christopher Peacocke’s A Study of Concepts Notes There Are No Recognitional Concepts--Not Even RED Introduction Compositionality Why Premise P is Plausible Objections Conclusion Afterword Acknowledgment Notes There Are No Recognitional Concepts--Not Even RED, Part 2: The Plot Thickens Introduction: The Story ’til Now Compositonality and Learnability Notes Do We Think in Mentalese? Remarks (...)
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  17.  32
    Constructional Preemption by Contextual Mismatch: A Corpus-Linguistic Investigation.Anatol Stefanowitsch - 2011 - Cognitive Linguistics 22 (1):107-129.
    The seeming absence of negative evidence in the input that children receive during language acquisition has long been regarded as a serious problem for non-nativist linguistic theories. Among the solutions that have been suggested for this problem, preemption by competing structures is doubtless the most intensively researched and widely accepted. However, while preemption works well in the domain of morphology, it cannot apply categorically in the domain of syntax, as this would preclude the existence of semantically overlapping constructions, (...)
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  18.  19
    What is the type-1/type-2 distinction?Nick Chater - 1997 - Behavioral and Brain Sciences 20 (1):68-69.
    Clark & Thornton's type-1/-2 distinction is not well-defined. The classes of type-1 and type-2 problems are too broad: many nocomputable functions are type-1 and type-2 learnable. They are also too narrow: trivial functions, such as identity, are neither type-1 nor type-2 learnable. Moreover, the scope of type-1 and type-2 problems appears to be equivalent. Overall, this distinction does not appear useful for machine learning or cognitive science.
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  19. Language Learning From Positive Evidence, Reconsidered: A Simplicity-Based Approach.Anne S. Hsu, Nick Chater & Paul Vitányi - 2013 - Topics in Cognitive Science 5 (1):35-55.
    Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes be corrected. Such learning from “positive evidence” has been viewed as raising “logical” problems for language acquisition. In particular, without correction, how is the child to recover from conjecturing an over-general grammar, which will be consistent with any sentence that the child hears? There have been many proposals concerning how this “logical problem” can be dissolved. In this study, we (...)
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  20. Complexity in Language Acquisition.Alexander Clark & Shalom Lappin - 2013 - Topics in Cognitive Science 5 (1):89-110.
    Learning theory has frequently been applied to language acquisition, but discussion has largely focused on information theoretic problems—in particular on the absence of direct negative evidence. Such arguments typically neglect the probabilistic nature of cognition and learning in general. We argue first that these arguments, and analyses based on them, suffer from a major flaw: they systematically conflate the hypothesis class and the learnable concept class. As a result, they do not allow one to draw significant conclusions about the learner. (...)
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  21.  15
    Reinforcement Learning for Production‐Based Cognitive Models.Adrian Brasoveanu & Jakub Dotlačil - 2021 - Topics in Cognitive Science 13 (3):467-487.
    We investigate how Reinforcement Learning methods can be used to solve the production selection and production ordering problem in ACT‐R. We focus on four algorithms from the Q learning family, tabular Q and three versions of Deep Q Networks, as well as the ACT‐R utility learning algorithm, which provides a baseline for the Q algorithms. We compare the performance of these five algorithms in a range of lexical decision tasks framed as sequential decision problems.
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  22.  71
    The routes of sense : thought, semantic underdeterminacy and compositionality.Walter B. Pedriali - unknown
    What does it mean to be a rational language user? What is it to obey linguistic rules? What is the proper account of linguistic competence? A Fregean answer to these questions would make essential appeal to the notion of sense: we are masters of a language to the extent that we are able to recognise the cognitive value of its expressions; we are rational judges regarding truth-value assignments to the extent that we are sensitive to the ways in which the (...)
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  23.  17
    Stream your brain! Speculative economy of the IoT and its pan-kinetic dataveillance.Sungyong Ahn - 2021 - Big Data and Society 8 (2).
    It is now a common belief that the truths of our lives are hidden in the databases streamed from our interactions in smart environments. In this current hype of big data, the Internet of Things has been suggested as the idea to embed small sensors and actuators everywhere to unfold the truths beneath the surfaces of everything. However, remaining the technology that promises more than it can provide thus far, more important for the IoT’s actual expansion to various social domains (...)
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  24.  43
    Making numbers out of magnitudes.Bradley J. Morris & Amy M. Masnick - 2008 - Behavioral and Brain Sciences 31 (6):662-663.
    We argue that number principles may be learnable instead of innate, by suggesting that children acquire probabilistically true number concepts rather than algorithms. We also suggest that non-propositional representational formats (e.g., mental models) may implicitly provide information that supports the induction of numerical principles. Given probabilistically true number concepts, the problem of the acquisition of mathematical principles is eliminated.
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  25.  34
    Simplified Graphical Domain-Specific Languages as Communication Tools in the Process of Developing Mobile Systems for Reporting Life-Threatening Situations – the Perspective of Technical Persons.Kamil Żyła - 2017 - Studies in Logic, Grammar and Rhetoric 51 (1):39-51.
    Reporting systems based on mobile technologies and feedback from regular citizens are becoming increasingly popular, especially as far as protection of environmental and cultural heritage is concerned. Reporting life-threatening situations, such as sudden natural disasters or traffic accidents, belongs to the same class of problems and could be aided by IT systems of a similar architecture. Designing and developing systems for reporting life-threatening situations is not a trivial task, requiring close cooperation between software developers and experts in different domains, who (...)
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  26.  26
    The Semantics and Pragmatics of Quotation.Paul Saka & Michael Johnson (eds.) - 2017 - Cham: Springer.
    The chapters in this volume address a variety of issues surrounding quotation, such as whether it is a pragmatic or semantic phenomenon, what varieties of quotation exist, and what speech acts are involved in quoting. Quotation poses problems for many prevailing theories of language. One fundamental principle is that for a language to be learnable, speakers must be able to derive the truth-conditions of sentences from the meanings of their parts. Another popular view is that indexical expressions like "I" display (...)
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  27.  92
    The incorporation of Moorean type information by introspective agents.Jiahong Guo - 2009 - Frontiers of Philosophy in China 4 (3):470-482.
    The main task is to discuss the issue in belief dynamics in which philosophical beliefs and rational introspective agents incorporate Moorean type new information. First, a brief survey is conducted on Moore’s Paradox, and one of its solutions is introduced with the help of Update Semantics. Then, we present a Dynamic Doxastic Logic (DDL) which revises the belief of introspective agents put forward by Lindström & Rabinowicz. Next, we attempt to incorporate Moorean type new information within the DEL (DDL) framework, (...)
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  28.  63
    Semantic holism and methodological constraints in the study of religion.Mark Q. Gardiner - 2016 - International Journal for Philosophy of Religion 79 (3):281-299.
    The methodology implicit in empirically grounded social scientific studies of religion naturally allies with forms of semantic holism. However, a well known argument which questions whether holism in general is consistent with the fact that languages are learnable can be extended into an epistemological one which questions whether holism is consistent with an empirical methodology. In other words, there is question whether holism, in fact, makes social science possible. I diagnose the assumptions on which that objection rests, pointing out that (...)
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  29.  17
    Effective Concept Classes of PAC and PACi Incomparable Degrees, Joins and Embedding of Degrees.Dodamgodage Gihanee M. Senadheera - 2023 - Bulletin of Symbolic Logic 29 (2):298-299.
    The Probably Approximately Correct (PAC) learning is a machine learning model introduced by Leslie Valiant in 1984. The PACi reducibility refers to the PAC reducibility independent of size and computation time. This reducibility in PAC learning resembles the reducibility in Turing computability. The ordering of concept classes under PAC reducibility is nonlinear, even when restricted to particular concrete examples.Due to the resemblance to Turing Reducibility, we suspected that there could be incomparable PACi and PAC degrees for the PACi and PAC (...)
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  30.  20
    Critique--the stakes of form.Sami R. Khatib (ed.) - 2020 - Zurich: Diaphanes.
    "Critique is a form of thinking and acting. It is determined by its objects, yet never accesses them immediately but is always mediated through its own forms of (re)presentation. Since the end of the 18th century, there has been a dynamization and fluidization of the understanding of form, as topoi such as the break, the marginalization, the tearing and opening indicate. However, these multifarious attempts to "build on the structure through demolition" (Benjamin) testify to the dependence of all articulation on (...)
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  31.  73
    The Relational Character of Belief.Andrew Ward - 1989 - Grazer Philosophische Studien 35 (1):73-82.
    In his book Scientific Realism and the Plasticity of Mind, Paul Churchland suggests that the singular terms for prepositional attitude predicates serve an adverbial function as elements of complex predicates. This view, called monadic adverbialism, has three problems. First the monadic predicates cannot be semantic primitives because this would compromise the learnability of the language containing them. Second, the account has no way to analyze general de dicto beliefs that does not compromise the language being learnable. Third, the account (...)
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  32.  17
    The Relational Character of Belief.Andrew Ward - 1989 - Grazer Philosophische Studien 35 (1):73-82.
    In his book Scientific Realism and the Plasticity of Mind, Paul Churchland suggests that the singular terms for prepositional attitude predicates serve an adverbial function as elements of complex predicates. This view, called monadic adverbialism, has three problems. First the monadic predicates cannot be semantic primitives because this would compromise the learnability of the language containing them. Second, the account has no way to analyze general de dicto beliefs that does not compromise the language being learnable. Third, the account (...)
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  33. Creative Polymathy and the COVID-19 Crisis.Michael Espindola Araki & Angela J. Cotellessa - 2020 - Frontiers in Psychology 11.
    It is increasingly argued that polymathy—vocational and avocational pursuits in multiple domains—is deeply associated with creativity and innovation, and that its development enables the creation of important bridges between otherwise fragmented, dispersed sets of knowledge. Nevertheless, the dominant culture in both industry and academia is still that of narrow specialization. In this paper, we argue that in the context of COVID-19 crisis, with its wicked and transdisciplinary nature, the disciplinary approach of specialization is ill-suited to solve our increasingly complex problems, (...)
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  34. Theories of Metaphor.Sherrill Jean Begres - 1986 - Dissertation, Wayne State University
    Metaphor, I argue, is a type of expression that is used to communicate information beyond that communicated by its literal meaning. I argue that the literal meaning of metaphors are essential. I attempt to account for metaphor in such a way as to retain the literal meaning, while also accounting for what is called the "metaphorical meaning" of metaphors. Secondly, I am concerned with the mechanisms in virtue of which we are able to distinguish the metaphorical from the literal. ;Chapter (...)
     
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  35.  89
    The structure of intrinsic complexity of learning.Sanjay Jain & Arun Sharma - 1997 - Journal of Symbolic Logic 62 (4):1187-1201.
    Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (from a graph of the function) have served as models for investigating the boundaries of learnability. Recently, a new approach to the study of "intrinsic" complexity of identification in the limit has been proposed. This approach, instead of dealing with the resource requirements of the learning algorithm, uses the notion of reducibility from recursion theory to (...)
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  36.  63
    Evolution and learning: An epistemological perspective. [REVIEW]Nello Cristianini - 1995 - Axiomathes 6 (3):429-437.
    The deep formal and conceptual link existing between artificial life and artificial intelligence can be highlighted using conceptual tools derived by Karl Popper's evolutionary epistemology.Starting from the observation that the structure itself of an organism embodies knowledge about the environment which it is adapted to, it is possible to regard evolution as a learning process. This process is subject to the same rules indicated by Popper for the growth of scientific knowledge: causal conjectures (mutations) and successive refutations (extinction). In the (...)
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  37.  19
    The learnability of natural concepts.Igor Douven - 2025 - Mind and Language 40 (1):120-135.
    According to a recent proposal, natural concepts are represented in an optimally designed similarity space, adhering to principles a skilled engineer would use for creatures with our perceptual and cognitive capacities. One key principle is that natural concepts should be easily learnable. While evidence exists for parts of this optimal design proposal, there has been no direct evidence linking naturalness to learning until now. This article presents results from a computational study on perceptual color space, demonstrating that naturalness indeed facilitates (...)
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  38.  99
    Learnability and Semantic Universals.Shane Steinert-Threlkeld & Jakub Szymanik - forthcoming - Semantics and Pragmatics.
    One of the great successes of the application of generalized quantifiers to natural language has been the ability to formulate robust semantic universals. When such a universal is attested, the question arises as to the source of the universal. In this paper, we explore the hypothesis that many semantic universals arise because expressions satisfying the universal are easier to learn than those that do not. While the idea that learnability explains universals is not new, explicit accounts of learning that (...)
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  39.  9
    Learnability and Linguistic Theory.Robert Matthews - 1989 - Springer.
    The impetus for this volume developed from the 1982 University of Western Ontario Learnability Workshop, which was organized by the editors and sponsored by that University's Department of Philosophy and the Centre for Cognitive Science. The volume e~plores the import of learnability theory for contemporary linguistic theory, focusing on foundational learning-theoretic issues associated with the parametrized Government-Binding framework. Written by prominent re searchers in the field, all but two of the eight contributions are pre viously unpublished. The editor's (...)
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  40. Learnability of state spaces of physical systems is undecidable.Petr Spelda & Vit Stritecky - 2024 - Journal of Computational Science 83 (December 2024):1-7.
    Despite an increasing role of machine learning in science, there is a lack of results on limits of empirical exploration aided by machine learning. In this paper, we construct one such limit by proving undecidability of learnability of state spaces of physical systems. We characterize state spaces as binary hypothesis classes of the computable Probably Approximately Correct learning framework. This leads to identifying the first limit for learnability of state spaces in the agnostic setting. Further, using the fact (...)
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  41.  82
    Contrafactives, Learnability, and Production.David Strohmaier & Simon Wimmer - 2025 - Experiments in Linguistic Meaning 3:395-410.
    No natural language has contrafactive attitude verbs. Because factives are universal across natural languages, this means that there is a major asymmetry between contrafactives and factives. We previously hypothesised that this asymmetry arises partly because the meaning of contrafactives is significantly harder to learn than that of factives. Here we test this hypothesis by using a production-oriented computational experiment that overcomes two limitations of our previous experiments. We find that our results do not support our previous hypothesis.
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  42.  65
    Learnability of Embedded Syntactic Structures Depends on Prosodic Cues.Jutta L. Mueller, Jörg Bahlmann & Angela D. Friederici - 2010 - Cognitive Science 34 (2):338-349.
    The ability to process center‐embedded structures has been claimed to represent a core function of the language faculty. Recently, several studies have investigated the learning of center‐embedded dependencies in artificial grammar settings. Yet some of the results seem to question the learnability of these structures in artificial grammar tasks. Here, we tested under which exposure conditions learning of center‐embedded structures in an artificial grammar is possible. We used naturally spoken syllable sequences and varied the presence of prosodic cues. The (...)
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  43.  74
    Learnability and compositionality.Douglas Patterson - 2005 - Mind and Language 20 (3):326–352.
    In recent articles Fodor and Lepore have argued that not only do considerations of learnability dictate that meaning must be compositional in the wellknown sense that the meanings of all sentences are determined by the meanings of a finite number of primitive expressions and a finite number of operations on them, but also that meaning must be 'reverse compositional' as well, in the sense that the meanings of the primitive expressions of which a complex expression is composed must be (...)
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  44.  63
    The learnability of abstract syntactic principles.Amy Perfors, Joshua B. Tenenbaum & Terry Regier - 2011 - Cognition 118 (3):306-338.
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  45.  80
    Learnability of Pregroup Grammars.Denis Béchet, Annie Foret & Isabelle Tellier - 2007 - Studia Logica 87 (2-3):225-252.
    This paper investigates the learnability by positive examples in the sense of Gold of Pregroup Grammars. In a first part, Pregroup Grammars are presented and a new parsing strategy is proposed. Then, theoretical learnability and non-learnability results for subclasses of Pregroup Grammars are proved. In the last two parts, we focus on learning Pregroup Grammars from a special kind of input called feature-tagged examples. A learning algorithm based on the parsing strategy presented in the first part is (...)
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  46. Contrafactives and Learnability.Simon Wimmer & David Strohmaier - 2022 - In Marco Degano, Tom Roberts, Giorgio Sbardolini & Marieke Schouwstra, Proceedings of the 23rd Amsterdam Colloquium. pp. 298-305.
    Richard Holton has drawn attention to a new semantic universal, according to which (almost) no natural language has contrafactive attitude verbs. This semantic universal is part of an asymmetry between factive and contrafactive attitude verbs. Whilst factives are abundant, contrafactives are scarce. We propose that this asymmetry is partly due to a difference in learnability. The meaning of contrafactives is significantly harder to learn than that of factives. We tested our hypothesis by conducting a computational experiment using an artificial (...)
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    Language Learnability in the Limit: A Generalization of Gold’s Theorem.Fernando C. Alves - 2023 - Journal of Logic, Language and Information 32 (3):363-372.
    In his pioneering work in the field of inductive inference, Gold (Inf Control 10:447–474, 1967) proved that a set containing all finite languages and at least one infinite language over the same fixed alphabet is not identifiable in the limit (learnable in the exact sense) from complete texts. Gold’s work paved the way for computational learning theories of language and has implications for two linguistically relevant classes in the Chomsky hierarchy (cf. Chomsky in Inf Control 2:137–167, 1959, Chomsky in Knowledge (...)
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    On Learnability of Restricted Classes of Categorial Grammars.Barbara Dziemidowicz-Gryz - 2007 - Studia Logica 85 (2):153-169.
    In this paper we present learning algorithms for classes of categorial grammars restricted by negative constraints. We modify learning functions of Kanazawa [10] and apply them to these classes of grammars. We also prove the learnability of intersection of the class of minimal grammars with the class of k-valued grammars.
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    Greater learnability is not sufficient to produce cultural universals.Anna N. Rafferty, Thomas L. Griffiths & Marc Ettlinger - 2013 - Cognition 129 (1):70-87.
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    Ostensive Learnability as a Test Criterion for Theory-Neutral Observation Concepts.Gerhard Schurz - 2015 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 46 (1):139-153.
    In the first part of my paper I discuss eight arguments in favour of the theory-dependence of observation: realistic content, guidance function of theories, perception as cognitive construction, expectation-dependence of perception, theory-dependence of scientific data, continuity between observational and theoretical concepts, language-dependence, and meaning holism. I argue that although these arguments make correct points, they do not exclude the existence of observations that are weakly theory-neutral in the sense that they don’t depend on acquired background knowledge. In the second part (...)
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