Dissertations / Theses: 'Inductive'

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Forsberg, Fredrik Nordvall. "Inductive-inductive definitions." Thesis, Swansea University, 2013. https://cronfa.swan.ac.uk/Record/cronfa43083.

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The principle of inductive-inductive definitions is a principle for defining data types in Martin-Lof Type Theory. It allows the definition of a set A, simultaneously defined w ith a family B : A → Set indexed over A. Such forms of definitions have been used by several authors in order to for example define the syntax of Type Theory in Type Theory itself. This thesis gives a theoretical justification for their use. We start by giving a finite axiomatisation of a type theory with inductive-inductive definitions in the style of Dybjer and Setzer's axiomatisation of inductive-recursive definitions. We then give a categorical characterisation of inductive-inductive definitions as initial objects in a certain category. This is presented using a general framework for elimination rules based on the concept of a Category with Families. To show consistency of inductive-inductive definitions, a set-theoretical model is constructed. Furthermore, we give a translation of our theory with a simplified form of the elimination rule into the already existing theory of indexed inductive definitions. This translation does not seem possible for the general elimination rule. Extensions to the theory are investigated, such as a combined theory of inductive-inductive-recursive definitions, more general forms of indexing and arbitrarily high (finite) towers of inductive-inductive definitions. Even so, not all uses of inductive-inductive definitions in the literature (in particular the syntax of Type Theory) are covered by the theories presented. Finally, two larger, novel case studies of the use of inductive-inductive definitions are presented: Conway's Surreal numbers and a formalisation of positive inductive-recursive definitions.

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Dijkstra, Gabe. "Quotient inductive-inductive definitions." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/42317/.

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In this thesis we present a theory of quotient inductive-inductive definitions, which are inductive-inductive definitions extended with constructors for equations. The resulting theory is an improvement over previous treatments of inductive-inductive and indexed inductive definitions in that it unifies and generalises these into a single framework. The framework can also be seen as a first approximation towards a theory of higher inductive types, but done in a set truncated setting. We give the type of specifications of quotient inductive-inductive definitions mutually with its interpretation as categories of algebras. A categorical characterisation of the induction principle is given and is shown to coincide with the property of being an initial object in the categories of algebras. From the categorical characterisation of induction, we derive a more type theoretic induction principle for our quotient inductive-inductive definitions that looks like the usual induction principles. The existence of initial objects in the categories of algebras associated to quotient inductive-inductive definitions is established for a class of definitions. This is done by a colimit construction that can be carried out in type theory itself in the presence of natural numbers, sum types and quotients or equivalently, coequalisers.

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KUSAKARI, Keiichirou, Masahiko SAKAI, and Toshiki SAKABE. "Primitive Inductive Theorems Bridge Implicit Induction Methods and Inductive Theorems in Higher-Order Rewriting." IEICE, 2005. http://hdl.handle.net/2237/9580.

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Hill, Alexandra. "Reasoning by analogy in inductive logic." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/reasoning-by-analogy-in-inductive-logic(039622d8-ab3f-418f-b46c-4d4e7a9eb6c1).html.

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This thesis investigates ways of incorporating reasoning by analogy into Pure (Unary) Inductive Logic. We start with an analysis of similarity as distance, noting that this is the conception that has received most attention in the literature so far. Chapter 4 looks in some detail at the consequences of adopting Hamming Distance as our measure of similarity, which proves to be a strong requirement. Chapter 5 then examines various adaptations of Hamming Distance and proposes a subtle modification, further-away-ness, that generates a much larger class of solutions.

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Lindblom, Adam. "Inductive Pulse Generation." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6699.

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Zebulske, Terry E. "Inductive Bible study methodology." Theological Research Exchange Network (TREN), 1988. http://www.tren.com.

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Kehris, Evangelos. "Incremental inductive interactive simulation." Thesis, Lancaster University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302936.

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Ray, Oliver. "Hybrid abductive inductive learning." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428111.

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Davies, Winton H. E. "Communication of inductive inference." Thesis, University of Aberdeen, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400670.

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This thesis addresses the question: "How can knowledge learnt through inductive inference be communicated in a multi-agent system?". Existing agent communication languages, such as KQML, assume logically sound inference methods. Unfortunately, induction is logically unsound. In general, machine learning techniques infer knowledge (or hypotheses) consistent with the locally available facts. However, in a multi-agent system, hypotheses learnt by one agent can directly contradict knowledge held by another. If an agent communicates induced knowledge as though it were logically sound, then the knowledge held by other agents in the community may become inconsistent. The answer we present in this thesis is that agents must, in general, communicate the bounds to such induced knowledge. The Version Space framework characterises inductive inference as a process which identifies the set of hypotheses that are consistent with both the observable facts and the constraints of the hypothesis description language. A Version Space can be expressed by two boundary sets, which represent the most general and most specific hypotheses. We thus propose that when communicating an induced hypothesis, that the hypothesis be bounded by descriptions of the most general and most specific hypotheses. In order to allow agents to integrate induced hypotheses with their own facts or their own induced hypotheses, the technique of Version Space Intersection can be used. We have investigated how boundary set descriptions can be generated for the common case of machine learning algorithms which learn hypotheses from unrestricted Version Spaces. This is a hard computational problem, as it is the equivalent of finding the minimal DNF description of a set of logical sentences. We consider four alternate approaches: exact minimization using the Quine-McCluskey algorithm; a naive, information-theoretic hill-climbing search; Espresso II, a sophisticated, heuristic logic minimization algorithm; and unsound approximation techniques. We demonstrate that none of these techniques are scalable to realistic machine learning problems.

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Pascoe, James. "The evoluation of 'Boxes' to quantized inductive learning : a study in inductive learning /." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-12172008-063016/.

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Pettersson, Emil. "Meta-Interpretive Learning Versus Inductive Metalogic Programming : A Comparative Analysis in Inductive Logic Programming." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-393291.

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Artificial intelligence and machine learning are fields of research that have become very popular and are getting more attention in the media as our computational power increases and the theories and latest developments of these fields can be put into practice in the real world. The field of machine learning consists of different paradigms, two of which are the symbolic and connectionist paradigms. In 1991 it was pointed out by Minsky that we could benefit from sharing ideas between the paradigms instead of competing for dominance in the field. That is why this thesis is investigating two approaches to inductive logic programming, where the main research goals are to, first: find similarities or differences between the approaches and potential areas where cross-pollination could be beneficial, and secondly: investigate their relative performance to each other based on the results published in the research. The approaches investigated are Meta-Interpretive Learning and Inductive Metalogic Programming, which belong to the symbolic paradigm of machine learning. The research is conducted through a comparative study based on published research papers. The conclusion to the study suggests that at least two aspects of the approaches could potentially be shared between them, namely the reversible aspect of the meta-interpreter and restricting the hypothesis space using the Herbrand base. However, the findings regarding performance were deemed incompatible, in terms of a fair one to one comparison. The results of the study are mainly specific, but could be interpreted as motivation for similar collaboration efforts between different paradigms.

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Passeraub, Philippe Alfons. "An integrated inductive proximity sensor /." Lausanne, 1999. http://library.epfl.ch/theses/?nr=1939.

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Bruin, Peter Johan de. "Inductive types in constructive languages." [S.l. : [Groningen] : s.n.] ; [University Library Groningen] [Host], 1995. http://irs.ub.rug.nl/ppn/128570415.

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Bella, Giampaolo. "Inductive verification of cryptographic protocols." Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621765.

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林謀楷 and Mau-kai Lam. "Inductive machine learning with bias." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31212426.

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Muggleton, Stephen H. "Inductive acquisition of expert knowledge." Thesis, University of Edinburgh, 1986. http://hdl.handle.net/1842/8124.

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Expert systems divide neatly into two categories: those in which ( 1) the expert decisions result in changes to some external environment (control systems), and (2) the expert decisions merely seek to describe the environment (classification systems). Both the explanation of computer-based reasoning and the "bottleneck" (Feigenbaum, 1979) of knowledge acquisition are major issues in expert systems research. We have contributed to these areas of research in two ways. Firstly, we have implemented an expert system shell, the Mugol environment, which facilitates knowledge acquisition by inductive inference and provides automatic explanation of run-time reasoning on demand. RuleMaster, a commercial version of this environment, has been used to advantage industrially in the construction and testing of two large classification systems. Secondly, we have investigated a new technique called sequence induction which can be used in the construction of control systems. Sequence induction is based on theoretical work in grammatical learning. We have improved existing grammatical learning algorithms as well as suggesting and theoretically characterising new ones. These algorithms have been successfully applied to the acquisition of knowledge for a diverse set of control systems, including inductive construction of robot plans and chess end-game strategies.

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Grimley, Allan. "Inductive types in functional programming." Thesis, University of Kent, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.253737.

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Massoud, Yehia Mahmoud 1968. "Simulation algorithms for inductive effects." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80593.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 105-110).
by Yehia Mahmoud Massoud.
Ph.D.

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Kemp, Charles Ph D. Massachusetts Institute of Technology. "The acquisition of inductive constraints." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/42074.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2008.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 197-216).
Human learners routinely make inductive inferences, or inferences that go beyond the data they have observed. Inferences like these must be supported by constraints, some of which are innate, although others are almost certainly learned. This thesis presents a hierarchical Bayesian framework that helps to explain the nature, use and acquisition of inductive constraints. Hierarchical Bayesian models include multiple levels of abstraction, and the representations at the upper levels place constraints on the representations at the lower levels. The probabilistic nature of these models allows them to make statistical inferences at multiple levels of abstraction. In particular, they show how knowledge can be acquired at levels quite remote from the data of experience--levels where the representations learned are naturally described as inductive constraints. Hierarchical Bayesian models can address inductive problems from many domains but this thesis focuses on models that address three aspects of high-level cognition. The first model is sensitive to patterns of feature variability, and acquires constraints similar to the shape bias in word learning. The second model acquires causal schemata--systems of abstract causal knowledge that allow learners to discover causal relationships given very sparse data. The final model discovers the structural form of a domain--for instance, it discovers whether the relationships between a set of entities are best described by a tree, a chain, a ring, or some other kind of representation. The hierarchical Bayesian approach captures several principles that go beyond traditional formulations of learning theory.
(cont.) It supports learning at multiple levels of abstraction, it handles structured representations, and it helps to explain how learning can succeed given sparse and noisy data. Principles like these are needed to explain how humans acquire rich systems of knowledge, and hierarchical Bayesian models point the way towards a modern learning theory that is better able to capture the sophistication of human learning.
by Charles Kemp.
Ph.D.

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20

Johansson, Moa. "Automated discovery of inductive lemmas." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/9807.

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The discovery of unknown lemmas, case-splits and other so called eureka steps are challenging problems for automated theorem proving and have generally been assumed to require user intervention. This thesis is mainly concerned with the automated discovery of inductive lemmas. We have explored two approaches based on failure recovery and theory formation, with the aim of improving automation of firstand higher-order inductive proofs in the IsaPlanner system. We have implemented a lemma speculation critic which attempts to find a missing lemma using information from a failed proof-attempt. However, we found few proofs for which this critic was applicable and successful. We have also developed a program for inductive theory formation, which we call IsaCoSy. IsaCoSy was evaluated on different inductive theories about natural numbers, lists and binary trees, and found to successfully produce many relevant theorems and lemmas. Using a background theory produced by IsaCoSy, it was possible for IsaPlanner to automatically prove more new theorems than with lemma speculation. In addition to the lemma discovery techniques, we also implemented an automated technique for case-analysis. This allows IsaPlanner to deal with proofs involving conditionals, expressed as if- or case-statements.

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Malatesta, Lorenzo. "Investigations into inductive-recursive definitions." Thesis, University of Strathclyde, 2015. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=24982.

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The theory of recursive functions where the domain of a function is inductively defined at the same time as the function is called induction-recursion. This theory has been introduced in Martin-Lèof type theory by Dybjer and further explored in a series of papers by Dybjer and Setzer. Important data types like universes closed under dependent type operators are instances of this theory. In this thesis we study the class of data types arising from inductive-recursive definitions, taking the seminal work of Dybjer and Setzer as our starting point. We show how the theories of inductive and indexed inductive types arise as sub-theories of induction-recursion, by revealing the role played by a notion of of size within the theory of induction-recursion. We then expand the expressive power of induction-recursion, showing how to extend the theory of induction-recursion in two different ways: in one direction we investigate the changes needed to obtain a more flexible semantics which gives rise to a more comprehensive elimination principle for inductive-recursive types. In another direction we generalize the theory of induction-recursion to a fibrational setting. In both extensions we provide a finite axiomatization of the theories introduced, we show applications and examples of these theories not previously covered by induction-recursion, and we justify the existence of data types built within these theories.

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McGarry, Theresa, and J. Mwinvelle. "Inductive Teaching for Oral Skills." Digital Commons @ East Tennessee State University, 2012. https://dc.etsu.edu/etsu-works/6153.

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Mawhinney, Linda. "Inductive limits of operator systems." Thesis, Queen's University Belfast, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707536.

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The aim of this thesis is to study inductive limits of operator systems. We begin by formalising the notion of the inductive limit for several categories related to, and including, the category of operator systems. Subsequently we observe how this structure interacts with other important operator system structures including tensor products, quotients and C*-extensions. Finally we have applied these results to inductive limits of graph operator systems. This has enabled the construction of an infinite graph operator system. Using this approach we have extended known results about graph operator systems to infinite graph operator systems.

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Heinz, Jeffrey Nicholas. "Inductive learning of phonotactic patterns." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1467886191&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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25

Tappert, Peter M. "Damage identification using inductive learning." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-05092009-040651/.

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Lam, Mau-kai. "Inductive machine learing with bias /." Hong Kong : University of Hong Kong, 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13972558.

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Groves, Teddy. "Let's reappraise Carnapian inductive logic!" Thesis, University of Kent, 2015. https://kar.kent.ac.uk/54023/.

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Ibrahim, Mohammad. "Wireless Inductive Charging for Electrical Vehicules : Electromagnetic Modelling and Interoperability Analysis." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112369/document.

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Le développement de la recharge sans contact de batteries comporte divers avantages pour les véhicules électriques. Cette solution est facile à utiliser, robuste et résistante aux intempéries par rapport aux câbles généralement utilisés. Le principe est basé sur le couplage magnétique entre un émetteur et un récepteur. L'objectif de cette thèse est de contribuer à proposer une norme pour permettre l’interopérabilité, c’est-à-dire, permettre à plusieurs émetteurs de fonctionner avec des récepteurs de différents fournisseurs. Comme le système doit aussi être tolérant au positionnement et doit respecter les recommandations concernant l’exposition humaine, de nombreuses configurations doivent être envisagées. Dans cette thèse, une modélisation avancée et fiable du système complet est proposée. La méthode des éléments finis est exploitée pour déterminer les caractéristiques électriques du coupleur inductif (inductances propres et mutuelles, facteur de couplage) dans différentes configurations de positionnement et d’interopérabilité. Ces valeurs permettent le dimensionnement du convertisseur à résonance. A ce stade différentes topologies de compensation sont considérées. Un modèle analytique au premier harmonique est mis en œuvre pour comparer les topologies et déterminer la fréquence de résonance globale du système. Un modèle circuit du système complet est ensuite développé pour évaluer précisément les courants et tensions. Enfin, un algorithme de régulation basé sur une méthode MPPT (Maximum Power Point Tracking) est évalué pour le réglage automatique de fréquence. A partir des courants calculés à la fréquence de résonance pour un point de fonctionnement nominal et grâce au modèle éléments finis incluant le châssis du véhicule le champ magnétique rayonné est calculé et comparé aux valeurs limites recommandées. A chaque étape de la modélisation, la sensibilité du système aux paramètres de configuration (positionnement, interopérabilité) est analysée. Des mesures effectuées au niveau du coupleur inductif et sur le système complet sont aussi utilisées dans l’analyse et permettent de valider le modèle
Development of contactless battery charging is an opportunity for electric vehicles. Compared to regular plugin cables, this solution is easy to use, robust and weather resistant. The power is transferred thanks to the magnetic coupling of inductive coils and a reduced magnetic circuit. The aim of this thesis is to contribute to propose a standard that would make possible to couple emitters with receivers from different suppliers, that is, to insure interoperability. As the system should also be tolerant to positioning and should respect human exposure recommendations, many configurations must be tested. In this thesis, an advanced and reliable modeling of the whole system is proposed. Using the finite element methods, the electrical characteristics (self, mutual inductances and coupling factor) of the inductive coupler are computed for different geometric and interoperability configurations. These values allow the dimensioning of the resonant converter. At this stage, different compensation topologies are considered. It is shown that the global resonant frequency can be derived and the topologies compared from a classical first harmonic approximation and analytical model. Then, a circuit model of the full system is developed in order to evaluate precisely the currents and voltages. Finally, the performance of a Maximum Power Point Tracking as frequency regulation algorithm is evaluated. From the currents computed at resonant frequency for the nominal operating point and the finite element model of the coupler, including the chassis of the vehicle, the radiated magnetic field is evaluated in order to check safety compliance. At each step of the modeling, the sensitivity of the system to the configuration parameters (positioning, interoperability) is analyzed. Measurements at the coupler level and for the full system are also used in this analysis and allow validating the model

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Badger, Julia. "An investigation into children's inductive reasoning strategies : what drives the development of category induction?" Thesis, Aston University, 2011. http://publications.aston.ac.uk/16300/.

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In a series of studies, I investigated the developmental changes in children’s inductive reasoning strategy, methodological manipulations affecting the trajectory, and driving mechanisms behind the development of category induction. I systematically controlled the nature of the stimuli used, and employed a triad paradigm in which perceptual cues were directly pitted against category membership, to explore under which circumstances children used perceptual or category induction. My induction tasks were designed for children aged 3-9 years old using biologically plausible novel items. In Study 1, I tested 264 children. Using a wide age range allowed me to systematically investigate the developmental trajectory of induction. I also created two degrees of perceptual distractor – high and low – and explored whether the degree of perceptual similarity between target and test items altered children’s strategy preference. A further 52 children were tested in Study 2, to examine whether children showing a perceptual-bias were in fact basing their choice on maturation categories. A gradual transition was observed from perceptual to category induction. However, this transition could not be due to the inability to inhibit high perceptual distractors as children of all ages were equally distracted. Children were also not basing their strategy choices on maturation categories. In Study 3, I investigated category structure (featural vs. relational category rules) and domain (natural vs. artefact) on inductive preference. I tested 403 children. Each child was assigned to either the featural or relational condition, and completed both a natural kind and an artefact task. A further 98 children were tested in Study 4, on the effect of using stimuli labels during the tasks. I observed the same gradual transition from perceptual to category induction preference in Studies 3 and 4. This pattern was stable across domains, but children developed a category-bias one year later for relational categories, arguably due to the greater demands on executive function (EF) posed by these stimuli. Children who received labels during the task made significantly more category choices than those who did not receive labels, possibly due to priming effects. Having investigated influences affecting the developmental trajectory, I continued by exploring the driving mechanism behind the development of category induction. In Study 5, I tested 60 children on a battery of EF tasks as well as my induction task. None of the EF tasks were able to predict inductive variance, therefore EF development is unlikely to be the driving factor behind the transition. Finally in Study 6, I divided 252 children into either a comparison group or an intervention group. The intervention group took part in an interactive educational session at Twycross Zoo about animal adaptations. Both groups took part in four induction tasks, two before and two a week after the zoo visits. There was a significant increase in the number of category choices made in the intervention condition after the zoo visit, a result not observed in the comparison condition. This highlights the role of knowledge in supporting the transition from perceptual to category induction. I suggest that EF development may support induction development, but the driving mechanism behind the transition is an accumulation of knowledge, and an appreciation for the importance of category membership.

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Sauvage, Emilien. "Modélisation numérique thermo-hydrodynamique et inductive d'une fonte verrière élaborée en creuset froid inductif." Grenoble INPG, 2007. http://www.theses.fr/2009INPG0147.

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Le but de ces travaux est la mise en place d'un modèle numérique simulant les phénomènes thermiques, hydrauliques et inductifs du procédé français de vitrification des déchets nucléaires. Du verre est élaboré dans un creuset froid inductif où opèrent un brassage par agitation mécanique et par bullage assurant une bonne homogénéité. La problématique est de nature multiphysique : induction directe, convection forcée et naturelle, écoulement diphasique. Les travaux ont porté d'une part sur le calcul de la répartition de la puissance Joule dans le verre de façon tridimensionnelle et d'autre part sur la prise en compte du brassage par bullage dans la fonte. Un couplage fort, tridimensionnel et itératif a été mis en place entre les logiciels Fluent@ et Flux@ pour modéliser les phénomènes électromagnétiques et thermohydrauliques couplés par les fortes variations des propriétés physiques du verre avec la température
The main goal of this work is to simulate thermal, hydraulic and inductive phenomena in the French nuc/ear waste vitrification process. Glass is melt in a cold crucible in which mechanical stirrer and air injection assure a good homogeneity of the load. This problem is multiphysical: direct induction in the glass, natural and forced convection, biphasic f/ow. Two research areas are achieved, the first is the calculation of the three-dimensional repartition of the Joule power in the molten glass, and the second is the simulation of the mixing by bubbling in the cast A strong, 3D and iterative coupling between the software FluxR and FluentR has been performed to simulate electromagnetic and thermo-hydraulic phenomena which are coupled due to the strong temperature dependence of the physical properties of the glass

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Ostrowski, Jörg. "Boundary element methods for inductive hardening." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=973933941.

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Nilsson, Jens. "Tree Transformations in Inductive Dependency Parsing." Licentiate thesis, Växjö University, School of Mathematics and Systems Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-1205.

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This licentiate thesis deals with automatic syntactic analysis, or parsing, of natural languages. A parser constructs the syntactic analysis, which it learns by looking at correctly analyzed sentences, known as training data. The general topic concerns manipulations of the training data in order to improve the parsing accuracy.

Several studies using constituency-based theories for natural languages in such automatic and data-driven syntactic parsing have shown that training data, annotated according to a linguistic theory, often needs to be adapted in various ways in order to achieve an adequate, automatic analysis. A linguistically sound constituent structure is not necessarily well-suited for learning and parsing using existing data-driven methods. Modifications to the constituency-based trees in the training data, and corresponding modifications to the parser output, have successfully been applied to increase the parser accuracy. The topic of this thesis is to investigate whether similar modifications in the form of tree transformations to training data, annotated with dependency-based structures, can improve accuracy for data-driven dependency parsers. In order to do this, two types of tree transformations are in focus in this thesis.

%This is a topic that so far has been less studied.

The first one concerns non-projectivity. The full potential of dependency parsing can only be realized if non-projective constructions are allowed, which pose a problem for projective dependency parsers. On the other hand, non-projective parsers tend, among other things, to be slower. In order to maintain the benefits of projective parsing, a tree transformation technique to recover non-projectivity while using a projective parser is presented here.

The second type of transformation concerns linguistic phenomena that are possible but hard for a parser to learn, given a certain choice of dependency analysis. This study has concentrated on two such phenomena, coordination and verb groups, for which tree transformations are applied in order to improve parsing accuracy, in case the original structure does not coincide with a structure that is easy to learn.

Empirical evaluations are performed using treebank data from various languages, and using more than one dependency parser. The results show that the benefit of these tree transformations used in preprocessing and postprocessing to a large extent is language, treebank and parser independent.

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Chu, Mabel. "Constructing transformation rules for inductive learning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0023/MQ51055.pdf.

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Wang, Yu. "Parallel inductive logic in data mining." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0019/MQ54492.pdf.

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Surkov, David. "Inductive confidence machine for pattern recognition." Thesis, Royal Holloway, University of London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412337.

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Baker, Ian Walter Shelley. "Inductive reasoning in persecutory delusional thought." Thesis, University of Plymouth, 1997. http://hdl.handle.net/10026.1/2404.

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Delusions are considered to be one of the primary symptoms of psychosis but until recently have received little empirical investigation. One approach has been to examine the extent to which deluded individuals demonstrate cognitive biases which are different from those of normal controls in inductive reasoning tasks. In this study two hypothesis testing tasks were used to investigate cognitive biases in a group of people with persecutory delusions compared to a group whose delusions had remitted and a normal control group. Participants completed two tasks consisting of a series of visual discrimination problems in which they had to choose between pairs of stimuli presented on cards. Condition 1 examined previously reported biases of deluded participants requiring less information before making judgements and being overconfident in their judgements. Positive or negative feedback was given after every card and participants were unconstrained in giving solutions. Condition 2 partially replicated Young and Bentall's (1995) hypothesis testing study and examined participants' ability to process information sequentially and progressively focus down the set of possible correct solutions. Feedback was restricted and participant responding was constrained. No differences were found between groups in condition 1. In condition 2 deluded participants produced fewer hypothesis and sampled from a smaller range of hypotheses than remitted and control participants. Deluded participants also produced fewer correct hypotheses than the other groups. A trend was found for deluded participants to use fewest sensible responses to feedback, followed by remitted and control groups. The reverse trend was found for use of nonsensical responses to feedback. Limitations of the study, implications for clinical practice and suggestions for future research are considered.

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Kit, Chun Yu. "Unsupervised lexical learning as inductive inference." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340205.

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Hill, Carla. "Mass assignments for inductive logic programming." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325748.

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Ronel, Tahel. "Symmetry principles in polyadic inductive logic." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/symmetry-principles-in-polyadic-inductive-logic(6bd9665b-b236-435c-9aad-7edb3cfc399e).html.

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We investigate principles of rationality based on symmetry in Polyadic Pure Inductive Logic. The aim of Pure Inductive Logic (PIL) is to determine how to assign probabilities to sentences of a language being true in some structure on the basis of rational considerations. This thesis centres on principles arising from instances of symmetry for sentences of first-order polyadic languages. We begin with the recently introduced Permutation Invariance Principle (PIP), and find that it is determined by a finite number of permutations on a finite set of formulae. We test the consistency of PIP with established principles of the subject and show, in particular, that it is consistent with Super Regularity. We then investigate the relationship between PIP and the two main polyadic principles thus far, Spectrum Exchangeability and Language Invariance, and discover there are close connections. In addition, we define the key notion of polyadic atoms as the building blocks of polyadic languages. We explore polyadic generalisations of the unary principle of Atom Exchangeability and prove that PIP is a natural extension of Atom Exchangeability to polyadic languages. In the second half of the thesis we investigate polyadic approaches to the unary version of Constant Exchangeability as invariance under signatures. We first provide a theory built on polyadic atoms (for binary and then general languages). We introduce the notion of a signature for non-unary languages, and principles of invariance under signatures, independence, and instantial relevance for this context, as well as a binary representation theorem. We then develop a second approach to these concepts using elements as alternative building blocks for polyadic languages. Finally, we introduce the concepts of homomorphisms and degenerate probability functions in Pure Inductive Logic. We examine which of the established principles of PIL are preserved by these notions, and present a method for reducing probability functions on general polyadic languages to functions on binary languages.

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Law, Mark. "Inductive learning of answer set programs." Thesis, Imperial College London, 2018. http://hdl.handle.net/10044/1/64824.

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The goal of Inductive Logic Programming (ILP) is to find a hypothesis that explains a set of examples in the context of some pre-existing background knowledge. Until recently, most research on ILP targeted learning definite logic programs. This thesis constitutes the first comprehensive work on learning answer set programs, introducing new learning frameworks, theoretical results on the complexity and generality of these frameworks, algorithms for learning ASP programs, and an extensive evaluation of these algorithms. Although there is previous work on learning ASP programs, existing learning frameworks are either brave -- where examples should be explained by at least one answer set -- or cautious where examples should be explained by all answer sets. There are cases where brave induction is too weak and cautious induction is too strong. Our proposed frameworks combine brave and cautious learning and can learn ASP programs containing choice rules and constraints. Many applications of ASP use weak constraints to express a preference ordering over the answer sets of a program. Learning weak constraints corresponds to preference learning, which we achieve by introducing ordering examples. We then explore the generality of our frameworks, investigating what it means for a framework to be general enough to distinguish one hypothesis from another. We show that our frameworks are more general than both brave and cautious induction. We also present a new family of algorithms, called ILASP (Inductive Learning of Answer Set Programs), which we prove to be sound and complete. This work concerns learning from both non-noisy and noisy examples. In the latter case, ILASP returns a hypothesis that maximises the coverage of examples while minimising the length of the hypothesis. In our evaluation, we show that ILASP scales to tasks with large numbers of examples finding accurate hypotheses even in the presence of high proportions of noisy examples.

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Mohd, Yusof Yuslinda. "Miniature magneto-inductive radio frequency sensors." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615702.

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Altenkirch, Thorsten. "Constructions, inductive types and strong normalization." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/11967.

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This thesis contains an investigation of Coquand's Calculus of Construction, a basic impredicative Type Theory. We review syntactic properties of the calculus, in particular decidability of equality and type-checking, based on the equality-as-judgement presentation. We present a set-theoretic notion of model, CC-structures, and use this to give a new strong normalisation proof based on a modification of the realizability interpretation. An extension of the core calculus by inductive types is investigated and we show, using the example of infinite trees, how the realizability semantics and the strong normalisation argument can be extended to non-algebraic inductive types. We emphasise that our interpretation is sound for large eliminations, e.g. allows the definition of sets by recursion. Finally we apply the extended calculus to a non-trivial problem: the formalization of the strong normalisation argument for Girard's System F. This formal proof has been developed and checked using the LEGO system, which has been implemented by Randy Pollack. We include the LEGO files in the appendix.

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Ko, Hsiang-Shang. "Analysis and synthesis of inductive families." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:2bc39bde-ce59-4a49-b499-3afdf174bbab.

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Based on a natural unification of logic and computation, Martin-Löf’s intuitionistic type theory can be regarded simultaneously as a computationally meaningful higher-order logic system and an expressively typed functional programming language, in which proofs and programs are treated as the same entities. Two modes of programming can then be distinguished: in externalism, we construct a program separately from its correctness proof with respect to a given specification, whereas in internalism, we encode the specification in a sophisticated type such that any program inhabiting the type also encodes a correctness proof, and we can use type information as a guidance on program construction. Internalism is particularly effective in the presence of inductive families, whose design can have a strong influence on program structure. Techniques and mechanisms for facilitating internalist programming are still lacking, however. This dissertation proposes that internalist programming can be facilitated by exploiting an interconnection between internalism and externalism, expressed as isomorphisms between inductive families into which data structure invariants are encoded and their simpler variants paired with predicates expressing those invariants. The interconnection has two directions: one analysing inductive families into simpler variants and predicates, and the other synthesising inductive families from simpler variants and specific predicates. They respectively give rise to two applications, one achieving a modular structure of internalist libraries, and the other bridging internalist programming with relational specifications and program derivation. The datatype-generic mechanisms supporting the applications are based on McBride’s ornaments. Theoretically, the key ornamental constructs — parallel composition of ornaments and relational algebraic ornamentation — are further characterised in terms of lightweight category theory. Most of the results are completely formalised in the Agda programming language.

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McGarry, Theresa, and J. Mwinyelle. "Inductive Language Teaching in Large Classes." Digital Commons @ East Tennessee State University, 2011. https://dc.etsu.edu/etsu-works/6165.

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Adjodah, Dhaval D. K. (Adjodlah Dhaval Dhamnidhi Kumar). "Social inductive biases for reinforcement learning." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/128415.

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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, September, 2019
Cataloged from the official PDF of thesis. "The Table of Contents does not accurately represent the page numbering"--Disclaimer page.
Includes bibliographical references (pages 117-126).
How can we build machines that collaborate and learn more seamlessly with humans, and with each other? How do we create fairer societies? How do we minimize the impact of information manipulation campaigns, and fight back? How do we build machine learning algorithms that are more sample efficient when learning from each other's sparse data, and under time constraints? At the root of these questions is a simple one: how do agents, human or machines, learn from each other, and can we improve it and apply it to new domains? The cognitive and social sciences have provided innumerable insights into how people learn from data using both passive observation and experimental intervention. Similarly, the statistics and machine learning communities have formalized learning as a rigorous and testable computational process.
There is a growing movement to apply insights from the cognitive and social sciences to improving machine learning, as well as opportunities to use machine learning as a sandbox to test, simulate and expand ideas from the cognitive and social sciences. A less researched and fertile part of this intersection is the modeling of social learning: past work has been more focused on how agents can learn from the 'environment', and there is less work that borrows from both communities to look into how agents learn from each other. This thesis presents novel contributions into the nature and usefulness of social learning as an inductive bias for reinforced learning.
I start by presenting the results from two large-scale online human experiments: first, I observe Dunbar cognitive limits that shape and limit social learning in two different social trading platforms, with the additional contribution that synthetic financial bots that transcend human limitations can obtain higher profits even when using naive trading strategies. Second, I devise a novel online experiment to observe how people, at the individual level, update their belief of future financial asset prices (e.g. S&P 500 and Oil prices) from social information. I model such social learning using Bayesian models of cognition, and observe that people make strong distributional assumptions on the social data they observe (e.g. assuming that the likelihood data is unimodal).
I were fortunate to collect one round of predictions during the Brexit market instability, and find that social learning leads to higher performance than when learning from the underlying price history (the environment) during such volatile times. Having observed the cognitive limits and biases people exhibit when learning from other agents, I present an motivational example of the strength of inductive biases in reinforcement learning: I implement a learning model with a relational inductive bias that pre-processes the environment state into a set of relationships between entities in the world. I observe strong improvements in performance and sample efficiency, and even observe the learned relationships to be strongly interpretable.
Finally, given that most modern deep reinforcement learning algorithms are distributed (in that they have separate learning agents), I investigate the hypothesis that viewing deep reinforcement learning as a social learning distributed search problem could lead to strong improvements. I do so by creating a fully decentralized, sparsely-communicating and scalable learning algorithm, and observe strong learning improvements with lower communication bandwidth usage (between learning agents) when using communication topologies that naturally evolved due to social learning in humans. Additionally, I provide a theoretical upper bound (that agrees with our empirical results) regarding which communication topologies lead to the largest learning performance improvement.
Given a future increasingly filled with decentralized autonomous machine learning systems that interact with humans, there is an increasing need to understand social learning to build resilient, scalable and effective learning systems, and this thesis provides insights into how to build such systems.
by Dhaval D.K. Adjodah.
Ph. D.
Ph.D. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences

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Abada, Hana. "Etude d'une décharge inductive de CF4." Paris 11, 2003. http://www.theses.fr/2003PA112129.

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Ce travail porte sur l'étude d'une décharge RF inductive de CF4. L'objectif était de comprendre les mécanismes de création et de perte des radicaux CFx qui jouent un rôle important dans la formation de dépôts sélectifs (préférentiellement sur Si ou Si3N4) de films polymères carbonofluorés (C:F) qui contribuent à la sélectivité mais aussi, à l'anisotropie de la gravure de couches de SiO2 avec arrêt sur des couches de Si ou de Si3N4. Au cours de ce travail, nous avons étudié deux phénomènes propres aux décharges inductives et leurs effets sur la dynamique des radicaux CF et CF2. Ces phénomènes sont le chauffage du gaz et l'apparition d'instabilités lors de la transition E-H (entre les modes capacitif et inductif de la décharge). Pour cela, nous avons utilisé la technique de Fluorescence Induite par Laser (FIL) comme diagnostic principal. Nous avons dans un premier temps caractérisé les instabilités en fonction des paramètres de la décharge. Nous avons ensuite mesuré par FIL, les variations des densités de CF et CF2 pendant les oscillations E-H et nous avons constaté que la cinétique de ces derniers est importante et ne peut être négligée dans les modèles décrivant ces instabilités. Nous avons mesuré par FIL de forts gradients de température du gaz dans notre décharge. Le mécanisme principal de chauffage du gaz est le pompage des niveaux vibrationels de CF4 par collisions électroniques, puis relaxation par transferts v-T. Enfin, nous avons étudié l'influence du chauffage du gaz sur le transport et la cinétique des radicaux CF et CF2. En tenant compte de l'effet de la thermo-diffusion, nous avons pu identifier les régions et les taux de création et de perte de ces radicaux dans l'état stationnaire et dans la post-décharge, à partir des profils de leurs fractions molaires (obtenus à partir des profils de densité mesurés par FIL). Nous avons également mis en évidence l'effet de la variation de la température sur les mesures de densité par FIL
This work presents the study of an RF inductive discharge in pure CF4. The overall aim was the investigation of CFx free radicals which are responsible for polymer films deposition. Polymerization is a key parameter in the selective etching of SiO2 layers over underlying Si or Si3N4. Two aspects of the inductive discharge and their effects on the CF and CF2 radical dynamics were investigated. These were the gas heating and the instability which occurs during the E-H transition (between the capacitive and the inductive mode of the discharge). Laser Induced Fluorescence (LIF) was the main diagnostic of the discharge. The instability was characterized for various discharge parameters. Time variation of radical densities during the E-H oscillations was measured. The CF and CF2 dynamics are significant and were included into a global model. Significant gas temperature gradients have been measured in the discharge. The main heating mechanism was found to be the excitation of the vibrational levels of CF4 by electronic collisions and then, the relaxation by v-T transfer. The effects of gas heating on the CF and CF2 transport and kinetics were studied. The thermo-diffusion effect has been taken into account in the investigation of the production and loss mechanisms of these radicals. The production and loss rates and their spatial dependence have been determined in the steady state and in the after-glow. In addition, we showed the effect of spatial neutral temperature variations on the radical density measurements using the LIF technique

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47

Shi, Guang Carleton University Dissertation Engineering Systems and Computer. "Inductive learning in network fault diagnosis." Ottawa, 1994.

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Chan, Christopher Wing Tai. "Magneto-inductive wave data communications systems." Thesis, University of Oxford, 2014. https://ora.ox.ac.uk/objects/uuid:014605c8-fc15-4166-a382-695042b05312.

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Metamaterials display unusual electromagnetic properties, such as, a negative effective permeability and negative effective permittivity. This has sparked much interest due to possibility of negative refraction which was later confirmed by experiments. The ability of magnetically coupled resonant circuits to display an effective permeability lead to the discovery of magneto-inductive waves. These waves are only supported on arrays of magnetically coupled resonant circuits. Research into magneto-inductive waves has been largely concentrated on their use in filters and their potential use in magnetic resonance imaging. However, some work has proposed the use of magneto-inductive waveguides as a data transfer medium. This report builds on previous work which found that an optimum existed for terminal-waveguide coupling, and aims to investigate the application of magneto-inductive waves in data transfer systems. A brief overview of the topic is given along with a description of the underlying characteristics. Factors that affect the capacity of magneto-inductive wave data transfer systems, such as inter element coupling, were identified. Two novel structures, both with the intent of increasing the bandwidth via different methods, are studied. One, by making a pseudo one-dimensional channel from a two-dimensional structure, and the other by using a dual-layer design to increase the coupling between adjacent elements. Both systems are modelled, using simple circuit theory and the impedance matrix method, and a comparison between simulated behaviour and experimental observation was made. There is discussion about the differences between experiment and simulation as well as their limitations. Magneto-inductive wave data transfer systems are eventually expected to support multiple terminals and as previous research only considered two-terminal systems, an investigation into the response of a one- and two-dimensional system with a blocking terminal was undertaken. The system was modelled, again using simple circuit theory and the impedance matrix method, and simulation and experiment were compared. As a whole, the simulations showed good agreement with experiments, after some initial adjustments. Both one- and two-dimensional systems showed that their performance was not severely effected by a blocking terminal. This suggests that magneto-inductive waveguides could support more terminals.

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Fisher, Anna Valeryevna. "Inductive generalization underlying mechanisms and developmental course /." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1117039741.

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Thesis (Ph.D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xii, 110 p.; also includes graphics. Includes bibliographical references (p. 103-110). Available online via OhioLINK's ETD Center

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Blaiklock, Philip. "A portable, wireless inductive-loop vehicle counter." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34737.

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This thesis descries the evolution and testing of a fully portable, inductive loop vehicle counter system. As a component of the NFS Embedded Distributed Simulation for Transportation System Management project, the system's cellular modem transmits real-time data to servers at Georgia Institute of Technology. From there, the data can be fed into simulations predicting travel behavior. Researchers revised both the detector circuit, and the temporary, reusable loop pad several times over multiple rounds of field testing. The final tested version of this system demonstrates the efficacy of uncommonly small inductive loops. When paired with a reliable data transmission channel, the system was shown to capture nearly 96% of actual through traffic.

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Dissertations / Theses on the topic 'Inductive'

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