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Dissertations / Theses on the topic 'Logic programming'
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1
Zhu, Biao. "Logic programming framework for resolution logics." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0006/MQ43411.pdf.
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McPhee, Richard. "Compositional logic programming." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.393413.
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Toni, Francesca. "Abductive logic programming." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490558.
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Hale, Roger William Stephen. "Programming in temporal logic." Thesis, University of Cambridge, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305467.
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Quintero, Jacinto Alfonso Davila. "Agents in logic programming." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263219.
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Moreno, Dávila Julio Moreno Davila Julio. "Mathematical programming for logic inference /." [S.l.] : [s.n.], 1990. http://library.epfl.ch/theses/?nr=784.
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Wetsel, Gerhard. "Abductive and constraint logic programming." Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/7212.
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Wang, Tzone I. "Distributed object oriented logic programming." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296891.
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Seres, Silvija. "The algebra of logic programming." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365466.
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Goldsmith, M. H. "Logic, programming and formal specification." Thesis, University of Oxford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371541.
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Ormerod, T. C. "Cognitive processes in logic programming." Thesis, University of Sunderland, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382171.
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Eshghi, Kave. "Meta-language in logic programming." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/38302.
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Sakama, Chiaki. "Studies on Disjunctive Logic Programming." Kyoto University, 1995. http://hdl.handle.net/2433/160755.
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本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものであるKyoto University (京都大学)
0048
新制・論文博士
博士(工学)
乙第8778号
論工博第2940号
新制||工||979(附属図書館)
UT51-95-B243
(主査)教授 堂下 修司, 教授 松本 吉弘, 教授 石田 亨
学位規則第4条第2項該当
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Bird, Philip. "Unifying programming paradigms : logic programming and finite state automata." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419609.
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Chen, Guiming. "Fuzzy FOIL: A fuzzy logic based inductive logic programming system." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/9621.
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In many domains, characterizations of a given attribute are imprecise, uncertain and incomplete in the available learning examples. The definitions of classes may be vague. Learning systems are frequently forced to deal with such uncertainty. Traditional learning systems are designed to work in the domains where imprecision and uncertainty in the data are absent. Those learning systems are limited because of their impossibility to cope with uncertainty--a typical feature of real-world data. In this thesis, we developed a fuzzy learning system which combines inductive learning with a fuzzy approach to solve problems arising in learning tasks in the domains affected by uncertainty and vagueness. Based on Fuzzy Logic, rather than pure First Order Logic used in FOIL, this system extends FOIL with learning fuzzy logic relation from both imprecise examples and background knowledge represented by Fuzzy Prolog. The classification into the positive and negative examples is allowed to be a degree (of positiveness or negativeness) between 0 and 1. The values of a given attribute in examples need not to be the same type. Symbolic and continuous data can exist in the same attribute, allowing for fuzzy unification (inexact matching). An inductive learning problem is formulated as to find a fuzzy logic relation with a degree of truth, in which a fuzzy gain calculation method is used to guide heuristic search. The Fuzzy FOIL's ability of learning the required fuzzy logic relations and dealing with vague data enhances FOIL's usefulness.
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Wichert, Carl-Alexander. "ULTRA - a logic transaction programming language." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=96114856X.
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Rajnovich, James Jacob. "Piilog, partial information ionic logic programming." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0016/NQ58159.pdf.
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Rochefort, Stephen. "Logic programming applications in educational environments." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0012/NQ61676.pdf.
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Fidjeland, Andreas Kirkeby. "Custom computer architectures for logic programming." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439777.
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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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Mukolera, J. "Logic programming in electrical machine design." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/47359.
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Bahgat, Reem. "Pandora : non-deterministic parallel logic programming." Thesis, Imperial College London, 1991. http://hdl.handle.net/10044/1/46657.
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Khabaza, Tom. "Towards AND/OR parallel logic programming." Thesis, University of Sussex, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283623.
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Cook, Jonathan J. "Language interoperability and logic programming languages." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/725.
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We discuss P#, our implementation of a tool which allows interoperation between a concurrent superset of the Prolog programming language and C#. This enables Prolog to be used as a native implementation language for Microsoft's .NET platform. P# compiles a linear logic extension of Prolog to C# source code. We can thus create C# objects from Prolog and use C#'s graphical, networking and other libraries. P# was developed from a modified port of the Prolog to Java translator, Prolog Cafe. We add language constructs on the Prolog side which allow concurrent Prolog code to be written. We add a primitive predicate which evaluates a Prolog structure on a newly forked thread. Communication between threads is based on the unification of variables contained in such a structure. It is also possible for threads to communicate through a globally accessible table. All of the new features are available to the programmer through new built-in Prolog predicates. We present three case studies. The first is an application which allows several users to modify a database. The users are able to disconnect from the database and to modify their own copies of the data before reconnecting. On reconnecting, conflicts must be resolved. The second is an object-oriented assistant, which allows the user to query the contents of a C# namespace or Java package. The third is a tool which allows a user to interact with a graphical display of the inheritance tree. Finally, we optimize P#'s runtime speed by translating some Prolog predicates into more idiomatic C# code than is produced by a naive port of Prolog Cafe. This is achieved by observing that semi-deterministic predicates (being those which always either fail or succeed with exactly one solution) that only call other semi-deterministic predicates enjoy relatively simple control flow. We make use of the fact that Prolog programs often contain predicates which operate as functions, and that such predicates are usually semi-deterministic.
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Dietz, Saldanha Emmanuelle-Anna. "From Logic Programming to Human Reasoning:." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-227412.
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Results of psychological experiments have shown that humans make assumptions, which are not necessarily valid, that they are influenced by their background knowledge and that they reason non-monotonically. These observations show that classical logic does not seem to be adequate for modeling human reasoning. Instead of assuming that humans do not reason logically at all, we take the view that humans do not reason classical logically. Our goal is to model episodes of human reasoning and for this purpose we investigate the so-called Weak Completion Semantics. The Weak Completion Semantics is a Logic Programming approach and considers the least model of the weak completion of logic programs under the three-valued Łukasiewicz logic.
As the Weak Completion Semantics is relatively new and has not yet been extensively investigated, we first motivate why this approach is interesting for modeling human reasoning. After that, we show the formal correspondence to the already established Stable Model Semantics and Well-founded Semantics. Next, we present an extension with an additional context operator, that allows us to express negation as failure. Finally, we propose a contextual abductive reasoning approach, in which the context of observations is relevant. Some properties do not hold anymore under this extension. Besides discussing the well-known psychological experiments Byrne’s suppression task and Wason’s selection task, we investigate an experiment in spatial reasoning, an experiment in syllogistic reasoning and an experiment that examines the belief-bias effect. We show that the results of these experiments can be adequately modeled under the Weak Completion Semantics. A result which stands out here, is the outcome of modeling the syllogistic reasoning experiment, as we have a higher prediction match with the participants’ answers than any of twelve current cognitive theories.
We present an abstract evaluation system for conditionals and discuss well-known examples from the literature. We show that in this system, conditionals can be evaluated in various ways and we put up the hypothesis that humans use a particular evaluation strategy, namely that they prefer abduction to revision. We also discuss how relevance plays a role in the evaluation process of conditionals. For this purpose we propose a semantic definition of relevance and justify why this is preferable to a exclusively syntactic definition. Finally, we show that our system is more general than another system, which has recently been presented in the literature.
Altogether, this thesis shows one possible path on bridging the gap between Cognitive Science and Computational Logic. We investigated findings from psychological experiments and modeled their results within one formal approach, the Weak Completion Semantics. Furthermore, we proposed a general evaluation system for conditionals, for which we suggest a specific evaluation strategy. Yet, the outcome cannot be seen as the ultimate solution but delivers a starting point for new open questions in both areas.
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Smaus, Jan-Georg. "Modes and types in logic programming." Thesis, University of Kent, 1999. https://kar.kent.ac.uk/21739/.
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This thesis deals with two themes: (1) construction of abstract domains for mode analysis of typed logic programs; (2) verification of logic programs using non-standard selection rules. (1) Mode information is important mainly for compiler optimisations. The precision of a mode analysis depends partly on the expressiveness of the abstract domain. We show how specialised abstract domains may be constructed for each type in a typed logic program. These domains capture the degree of instantiation of a term very precisely. The domain construction procedure is implemented using the Godel language and tested on some example programs to demonstrate the viability and high precision of the analysis. (2) We provide verification methods for logic programs using selection rules other than the usual left-to-right selection rule. We consider five aspects of verification: termination; and freedom from (full) unification, occur-check, foundering, and errors related to built-ins. The methods are based on assigning a mode, input or output, to each argument position of each predicate. This mode is only fixed with respect to a particular execution. For termination, we first identify a class of predicates which terminate under the assumption that derivations are input-consuming, meaning that in each derivation step, the input arguments of the selected atom do not become instantiated. Input-consuming derivations can be realised using block declarations, which test that certain argument positions of the selected atom are non-variable. To show termination for a program where not all predicates terminate under the assumption that derivations are input-consuming, we make the stronger assumption that derivations are left-based. This formalises the ''default left-to-right'' selection rule of Prolog. To the best of our knowledge, this work is the first formal and comprehensive approach to this kind of termination problem. The results on the other four aspects are mainly generalisations of previous results assuming the left-to-right selection rule.
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Lin, Dianhuan. "Logic programs as declarative and procedural bias in inductive logic programming." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/24553.
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Machine Learning is necessary for the development of Artificial Intelligence, as pointed out by Turing in his 1950 article ``Computing Machinery and Intelligence''. It is in the same article that Turing suggested the use of computational logic and background knowledge for learning. This thesis follows a logic-based machine learning approach called Inductive Logic Programming (ILP), which is advantageous over other machine learning approaches in terms of relational learning and utilising background knowledge. ILP uses logic programs as a uniform representation for hypothesis, background knowledge and examples, but its declarative bias is usually encoded using metalogical statements. This thesis advocates the use of logic programs to represent declarative and procedural bias, which results in a framework of single-language representation. We show in this thesis that using a logic program called the top theory as declarative bias leads to a sound and complete multi-clause learning system MC-TopLog. It overcomes the entailment-incompleteness of Progol, thus outperforms Progol in terms of predictive accuracies on learning grammars and strategies for playing Nim game. MC-TopLog has been applied to two real-world applications funded by Syngenta, which is an agriculture company. A higher-order extension on top theories results in meta-interpreters, which allow the introduction of new predicate symbols. Thus the resulting ILP system Metagol can do predicate invention, which is an intrinsically higher-order logic operation. Metagol also leverages the procedural semantic of Prolog to encode procedural bias, so that it can outperform both its ASP version and ILP systems without an equivalent procedural bias in terms of efficiency and accuracy. This is demonstrated by the experiments on learning Regular, Context-free and Natural grammars. Metagol is also applied to non-grammar learning tasks involving recursion and predicate invention, such as learning a definition of staircases and robot strategy learning. Both MC-TopLog and Metagol are based on a 'top'-directed framework, which is different from other multi-clause learning systems based on Inverse Entailment, such as CF-Induction, XHAIL and IMPARO. Compared to another 'top'-directed multi-clause learning system TAL, Metagol allows the explicit form of higher-order assumption to be encoded in the form of meta-rules.
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Singhi, Soumya. "Computing stable models of logic programs." Lexington, Ky. : [University of Kentucky Libraries], 2003. http://lib.uky.edu/ETD/ukycosc2003t00117/SSThesis.pdf.
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Thesis (M.S.)--University of Kentucky, 2003.Title from document title page (viewed June 21, 2004). Document formatted into pages; contains viii, 55 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 52-54).
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Lin, Nai-Wei. "Automatic complexity analysis of logic programs." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186287.
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This dissertation describes research toward automatic complexity analysis of logic programs and its applications. Automatic complexity analysis of programs concerns the inference of the amount of computational resources consumed during program execution, and has been studied primarily in the context of imperative and functional languages. This dissertation extends these techniques to logic programs so that they can handle nondeterminism, namely, the generation of multiple solutions via backtracking. We describe the design and implementation of a (semi)-automatic worst-case complexity analysis system for logic programs. This system can conduct the worst-case analysis for several complexity measures, such as argument size, number of solutions, and execution time. This dissertation also describes an application of such analyses, namely, a runtime mechanism for controlling task granularity in parallel logic programming systems. The performance of parallel systems often starts to degrade when the concurrent tasks in the systems become too fine-grained. Our approach to granularity control is based on time complexity information. With this information, we can compare the execution cost of a procedure with the average process creation overhead of the underlying system to determine at runtime if we should spawn a procedure call as a new concurrent task or just execute it sequentially. Through experimental measurements, we show that this mechanism can substantially improve the performance of parallel systems in many cases. This dissertation also presents several source-level program transformation techniques for optimizing the evaluation of logic programs containing finite-domain constraints. These techniques are based on number-of-solutions complexity information. The techniques include planning the evaluation order of subgoals, reducing the domain of variables, and planning the instantiation order of variable values. This application allows us to solve a problem by starting with a more declarative but less efficient program, and then automatically transforming it into a more efficient program. Through experimental measurements we show that these program transformation techniques can significantly improve the efficiency of the class of programs containing finite-domain constraints in most cases.
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Athakravi, Duangtida. "Inductive logic programming using bounded hypothesis space." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/33798.
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Inductive Logic Programming (ILP) systems apply inductive learning to an inductive learning task by deriving a hypothesis which explains the given examples. Applying ILP systems to real applications poses many challenges as they require large search space, noise is present in the learning task, and in domains such as software engineering hypotheses are required to satisfy domain specific syntactic constraints. ILP systems use language biases to define the hypothesis space, and learning can be seen as a search within the defined hypothesis space. Past systems apply search heuristics to traverse across a large hypothesis space. This is unsuitable for systems implemented using Answer Set Programming (ASP), for which scalability is a constraint as the hypothesis space will need to be grounded by the ASP solver prior to solving the learning task, making them unable to solve large learning tasks. This work explores how to learn using bounded hypothesis spaces and iterative refinement. Hypotheses that explain all examples are learnt by refining smaller partial hypotheses. This improves the scalability of ASP based systems as the learning task is split into multiple smaller manageable refinement tasks. The thesis presents how syntactic integrity constraints on the hypothesis space can be used to strengthen hypothesis selection criteria, removing hypotheses with undesirable structure. The notion of constraint-driven bias is introduced, where hypotheses are required to be acceptable with respect to the given meta-level integrity constraints. Building upon the ILP system ASPAL, the system RASPAL which learns through iterative hypothesis refinement is implemented. RASPAL's algorithm is proven, under certain assumptions, to be complete and consistent. Both systems have been applied to a case study in learning user's behaviours from data collected from their mobile usage. This demonstrates their capability for learning with noise, and the difference in their efficiency. Constraint-driven bias has been implemented for both systems, and applied to a task in specification revision, and in learning stratified programs.
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Wu, Cheng-min, of Western Sydney Nepean University, and School of Computing and Information Technology. "Implementing a prioritized logic programming system : thesis." THESIS_XXX_CIT_Wu_C.xml, 2000. http://handle.uws.edu.au:8081/1959.7/188.
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Rule based knowledge representation and reasoning often face a problem of conflict with rules. One common way of solving conflicts is to introduce priorities associate with rules. The thesis describes the underlying algorithm to implement prioritized logic programs (PLPs) proposed by Zhang and Foo in 1997. PLPs are proposed as an extension of Gelfond and Lifschitz's extended logic programs by introducing preferences associatied with rules to the program, where answer sets provide a semantics of PLPs. Major algorithms are presented in detail, and how answer sets can be derived from the algorithm demonstrated. Under this implementation, a PLP is computed efficiently based on previous Niemela and Simons' method of computing stable models of logic programs. Finally, world wide web interface has been employed and embedded to the system to provide great accessibility to the public.Master of Science (Hons) (Computing)
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Gaubatz, Donald Almo. "Logic programming analysis of asynchronous digital circuits." Thesis, University of Cambridge, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386062.
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Quigley, Claire Louise. "A programming logic for Java bytecode programs." Thesis, University of Glasgow, 2004. http://theses.gla.ac.uk/3030/.
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One significant disadvantage of interpreted bytecode languages, such as Java, is their low execution speed in comparison to compiled languages like C. The mobile nature of bytecode adds to the problem, as many checks are necessary to ensure that downloaded code from untrusted sources is rendered as safe as possible. But there do exist ways of speeding up such systems. One approach is to carry out static type checking at load time, as in the case of the Java Bytecode Verifier. This reduces the number of runtime checks that must be done and also allows certain instructions to be replaced by faster versions. Another approach is the use of a Just In Time (JIT) Compiler, which takes the bytecode and produces corresponding native code at runtime. Some JIT compilers also carry out some code optimization. There are, however, limits to the amount of optimization that can safely be done by the Verifier and JITs; some operations simply cannot be carried out safely without a certain amount of runtime checking. But what if it were possible to prove that the conditions the runtime checks guard against would never arise in a particular piece of code? In this case it might well be possible to dispense with these checks altogether, allowing optimizations not feasible at present. In addition to this, because of time constraints, current JIT compilers tend to produce acceptable code as quickly as possible, rather than producing the best code possible. By removing the burden of analysis from them it may be possible to change this. We demonstrate that it is possible to define a programming logic for bytecode programs that allows the proof of bytecode programs containing loops. The instructions available to use in the programs are currently limited, but the basis is in place to extend these. The development of this logic is non-trivial and addresses several difficult problems engendered by the unstructured nature of bytecode programs.
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Andrews, James H. "Logic programming : operational semantics and proof theory." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/13484.
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Logic programming systems which use parallel strategies for computing 'and' and 'or' are theoretically elegant, but systems which use sequential strategies are far more widely used and do not fit well into the traditional theory of logic programming. This thesis presents operational and proof-theoreticcharacterisations for systems having each of the possible combinations of parallel or sequential 'and' and parallel or sequential 'or'. The operational semantics are in the form of an abstract machine. The four control strategies emerge as simple variants of this machine with varying degrees of determinism; some of these variants have equivalent, compositional operational semantics, which are given. The proof-theoretic characterisations consist of a single central sequent calculus, LKE (similar to Gentzen's sequent calculus for classical first order logic), and sets of axioms which capture the success or failure of queries in the four control strategies in a highly compositional, logical way. These proof-theoretic characterisations can be seen as logical semantics of the logic programming languages. The proof systems can also be used in practice to prove more general properties of logic programs, although it is shown that they are unavoidably incomplete for this purpose. One aspect of this incompleteness is that it is not possible to derive all valid sequents having free variables; however, induction rules are given which can help to prove many useful sequents of this kind.
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Dayantis, George. "Types, modularisation and abstraction in logic programming." Thesis, University of Sussex, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.255977.
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Ebrahim, Rafee E. "Fuzzy logic programming based on alpha-cuts." Thesis, De Montfort University, 2003. http://hdl.handle.net/2086/13274.
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Corapi, Domenico. "Nonmonotonic inductive logic programming as abductive search." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/9814.
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Inductive Logic Programming (ILP) is a machine learning technique that relies on logic programs as a representation language. Most of the effort in the field of ILP has concentrated on a restricted class of problems, providing solutions that do not fully support negation. On the other hand, integration of negation and nonmonotonic reasoning in logic programming is common and important for a number of problems. This thesis presents an approach to nonmonotonic ILP that is based on a transformation of the original problem to a problem that can be solved by employing abductive reasoning. In particular we present a general framework for the transformation that can be used as reference for concrete implementations. We instantiate the transformation to derive two alternative implementations that are rooted in the two dominant computational logic paradigms: Prolog and Answer Set Programming (ASP). In the first case, we derive an implementation, called TAL, that is based on the abductive proof procedure SLDNFA and uses a customisable best-first search on the space of abductive solutions. In the second case the transformation is further refined in order to exploit the computational properties of available ASP solvers. In the proposed system called ASPAL, a theory is constructed from a set of mode declarations and used to extend the search of the underlying solver, so enabling the derivation of inductive hypotheses. We provide completeness and soundness results for the framework and the ILP systems presented and show how, as a consequence of this, it is possible to induce complex multi-predicate hypotheses involving negation, recursion and the definition of elements of the domain that are not directly observed. We validate the framework on established ILP benchmark problems, on some nonmonotonic ILP problems proposed in the literature. Furthermore we demonstrate the approach on a novel application of nonmonotonic ILP to the revision of normative frameworks.
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Wu, Cheng-min. "Implementing a prioritized logic programming system : thesis." Thesis, View thesis, 2000. http://handle.uws.edu.au:8081/1959.7/188.
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Rule based knowledge representation and reasoning often face a problem of conflict with rules. One common way of solving conflicts is to introduce priorities associate with rules. The thesis describes the underlying algorithm to implement prioritized logic programs (PLPs) proposed by Zhang and Foo in 1997. PLPs are proposed as an extension of Gelfond and Lifschitz's extended logic programs by introducing preferences associatied with rules to the program, where answer sets provide a semantics of PLPs. Major algorithms are presented in detail, and how answer sets can be derived from the algorithm demonstrated. Under this implementation, a PLP is computed efficiently based on previous Niemela and Simons' method of computing stable models of logic programs. Finally, world wide web interface has been employed and embedded to the system to provide great accessibility to the public.
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Wu, Cheng-min. "Implementing a prioritized logic programming system : thesis /." View thesis, 2000. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030618.084318/index.html.
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Thesis (MSc (Hons.)) -- University of Western Sydney, Nepean, 2000."A thesis submitted for the degree of Master of Science (Honours)-Computing at University of Western Sydney - Nepean" Includes bibliographical references (leaves 117-121).
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CATTAFI, Massimiliano. "LOGIC AND CONSTRAINT PROGRAMMING FOR COMPUTATIONAL SUSTAINABILITY." Doctoral thesis, Università degli studi di Ferrara, 2012. http://hdl.handle.net/11392/2388775.
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Computational Sustainability is an interdisciplinary field that aims to develop computational
and mathematical models and methods for decision making concerning
the management and allocation of resources in order to help solve environmental
problems.
This thesis deals with a broad spectrum of such problems (energy efficiency, water
management, limiting greenhouse gas emissions and fuel consumption) giving
a contribution towards their solution by means of Logic Programming (LP) and
Constraint Programming (CP), declarative paradigms from Artificial Intelligence
of proven solidity.
The problems described in this thesis were proposed by experts of the respective
domains and tested on the real data instances they provided. The results are encouraging
and show the aptness of the chosen methodologies and approaches.
The overall aim of this work is twofold: both to address real world problems
in order to achieve practical results and to get, from the application of LP and
CP technologies to complex scenarios, feedback and directions useful for their
improvement.
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AZZOLINI, DAMIANO. "Extensions and Applications of Probabilistic Logic Programming." Doctoral thesis, Università degli studi di Ferrara, 2022. http://hdl.handle.net/11392/2478826.
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L'intelligenza artificiale simbolica viene definita come ''Good Old-Fashioned Artificial Intelligence'' perché rappresenta ciò che è noto tramite simboli (per esempio, predicati del primo ordine e costanti) invece che tramite matrici di numeri, come accade per le soluzioni sub-simboliche (principalmente reti neurali).
Nonostante il recente predominio delle reti neurali, considerate quasi una panacea per risolvere qualsiasi problema legato all'apprendimento automatico, esiste un ambito di ricerca in rapida espansione chiamato Statistical Relational Artificial Intelligence dove l'obiettivo è quello di combinare ragionamento logico ed incertezza per rappresentare ed estrarre conoscenza da domini complessi.
Tra i possibili formalismi, la Programmazione Logico Probabilistica (PLP) sta suscitando molto interesse grazie alla possibilità di integrare logica e probabilità.
Il lavoro presentato in questa dissertazione è strutturato in due parti.
Nella prima parte vengono analizzate diverse estensioni per PLP che ampliano i possibili scenari applicativi.
In particolare, vengono analizzati programmi logico probabilistici ibridi che presentano sia variabili continue che discrete.
Per questi, viene fornita una nuova semantica ben definita.
Successivamente, vengono introdotti programmi logico probabilistici abduttivi, che estendono PLP con la possibilità di gestire dati incompleti, ottimizzabili e riducibili, dove viene utilizzata la programmazione a vincoli per apprendere i parametri e la struttura di programmi logico probabilistici con vincoli.
L'introduzione di queste nuove classi è motivata da diverse possibili applicazioni discusse nelle corrispondenti sezioni.
Per ciascuna nuova estensione, viene definito formalmente il problema che si vuole risolvere e vengono forniti algoritmi per effettuare inferenza.
La seconda parte è incentrata sulla rappresentazione tramite PLP e programmi ibridi di scenari tipici di sistemi blockchain.
Vengono discussi modelli per analizzare le commissioni associate alle transazioni, smart contract, double spending e la rete Lightning Network.Symbolic Artificial Intelligence has been considered ''Good Old-Fashioned Artificial Intelligence'' since it usually represents knowledge through explicit symbols, such as first-order logic predicates and constants, instead of through large numeric matrices, as happens for sub-symbolic solutions, namely, neural networks. Despite the recent predominance of neural networks, considered almost a silver bullet for solving every machine learning problem, there is still an ever-growing field of research called Statistical Relational Artificial Intelligence, where the goal is to combine logic and uncertainty to represent and reason over complex domains. Among all the several possible formalisms, Probabilistic Logic Programming (PLP) is gaining traction thanks to its ability to integrate logical and probabilistic reasoning. The work presented in this dissertation is structured in two parts. In the first, we present several extensions of PLP to widen the possible application scenarios. In particular, we review hybrid probabilistic logic programs, where continuous and discrete random variables coexist, and provide a new well-defined semantics. After this, we introduce probabilistic abductive logic programs, where we extend PLP with the possibility to reason with incomplete data, and probabilistic optimizable and reducible logic programs, where we leverage constraint programming to learn the parameters and the structure of probabilistic logic programs subject to constraints. The definition of these new classes is motivated by real-world examples discussed in the correspondent chapters. For all of these proposals, we formally introduce the task to solve and provide practical inference algorithms. The second part is focused on the adoption of PLP and hybrid probabilistic logic programs to model several blockchain-related scenarios. We discuss models to analyse transaction fees, smart contracts, double spending, and the Lightning Network.
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Farrow, P. F. "Logic, dependencies, and specification engineering." Thesis, University of Southampton, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328298.
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Duan, Zhenhua. "An extended interval temporal logic and a framing technique for temporal logic programming." Thesis, University of Newcastle Upon Tyne, 1996. http://hdl.handle.net/10443/2075.
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Temporal logic programming is a paradigm for specification and verification of concurrent programs in which a program can be written, and the properties of the program can be described and verified in a same notation. However, there are many aspects of programming in temporal logics that are not well-understood. One such an aspect is concurrent programming, another is framing and the third is synchronous communication for parallel processes. This thesis extends the original Interval Temporal Logic (ITL) to include infinite models, past operators, and a new projection operator for dealing with concurrent computation, synchronous communication, and framing in the context of temporal logic programming. The thesis generalizes the original ITL to include past operators such as previous and past chop, and extends the model to include infinite intervals. A considerable collection of logic laws regarding both propositional and first order logics is formalized and proved within model theory. After that, a subset of the extended ITL is formalized as a programming language, called extended Tempura. These extensions, as in their logic basis, include infinite models, the previous operator, projection and framing constructs. A normal form for programs within the extended Tempura is demonstrated. Next, a new projection operator is introduced. In the new construct, the sub-processes are autonomous; each process has the right to specify its own interval over which it is executed. The thesis presents a framing technique for temporal logic programming, which includes the definitions of new assignments, the assignment flag and the framing operator, the formalization of algebraic properties of the framing operator, the minimal model semantics of framed programs, as well as an executable framed interpreter. The synchronous communication operator await is based directly on the proposed framing technique. It enables us to deal with concurrent computation. Based on EITL and await operator, a framed concurrent temporal logic programming language, FTLL, is formally defined within EITL. Finally, the thesis describes a framed interpreter for the extended Tempura which has been developed in SICSTUS prolog. In the new interpreter, the implementation of new assignments, the frame operator, the await operator, and the new projection operator are all included.
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Wong, Ka-Shu Computer Science & Engineering Faculty of Engineering UNSW. "Forgetting in logic programs." Publisher:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/43732.
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Forgetting is an operation which removes information from a set of logical statements, such that a) the language used by the logic is simplified; and b) as much information as possible from the original logical statements are preserved. Forgetting operations are useful in a variety of contexts, including knowledge representation, where it is necessary to have an operation for removing information from knowledge bases; and the problem of relevance, where logical statements are simplified by removing irrelevant information. In this thesis we consider forgetting operations on logic programs with negation-as-failure according to the stable model semantics. There are existing notions of forgetting on logic programs in the literature: the strong forgetting and weak forgetting of Zhang and Foo, and the semantic approach to forgetting introduced by Wang et al. However, these notions are inadequate: the strong and weak forgettings are defined syntactically with no obvious connections to semantic notions of forgetting; while the semantic approach of Wang et al. does not take into account ``hidden'' information encoded in unused rules. The idea of equivalence on logic programs capture the extent of information contained in a logic program. We consider that two logic programs are equivalent iff the two programs contain the same information. For logic programs, there are many different possible notions of equivalence. We look at the well-known notion of strong equivalence and a new notion of equivalence which we call T-equivalence. Associated with each of these equivalences is a consequence relation on logic program rules. We present sound and complete set of inference rules for both consequence relations. We present a novel approach to logic program forgetting which uses as its basis a set of postulates, which are defined relative to a notion of equivalence. We show that if we use T-equivalence as the equivalence relation, then the only possible forgetting operations (up to equivalence) are strong forgetting and weak forgetting. If strong equivalence is used instead, then there are also only two possible forgetting operations (up to equivalence).
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Padmanabhuni, Srinivas. "Logic programming with stable models for constraint satisfaction." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0009/NQ60011.pdf.
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Melendez, Rafael Ramirez. "A logic-based concurrent object-oriented programming language." Thesis, University of Bristol, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337487.
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ALVES, MARIA DO CARMO ELIAS. "A LOGIC PROGRAMMING EXTENSION FOR C CALLED CLOG." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1993. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8753@1.
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A aplicação de linguagens declarativas baseadas na
programação em lógica tem sido bastante difundida devido
ao grande interesse hoje existente na área de
Inteligência
Artificial. Porém, o uso destas linguagens ainda não é
muito evidente devido à restrições de desempenho,
portabilidade, capacidade de integração com outras
linguagens, etc. O presente trabalho contém a definição
e
implementação de uma extensão de programação em lógica
para o C, denominada CLog, que têm como objetivo suprir
as
deficiências acima, permitindo, principalmente, a
implementação de aplicações que apresentem
características
de programação em lógica integrada à programação
imperativa em um mesmo ambiente de desenvolvimento.The use of declarative languages based in logic programming has been spread out due to the great interest in Artificial Intelligence. However, the use of these languages is not evident yet due to performance, portability, integration to other languages capability and other restrictions. This work contains the definition and implementation of a logic programming extension for C called Clog, which intends to cover the above deficiencies, allowing, mainly, the implementation of applications that have logic programming characteristics integrated to interative programming in the same development environment.
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FILHO, DANTE CORBUCCI. "LISPLOG: A LANGUAGE FOR FUNCTIONAL AND LOGIC PROGRAMMING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1989. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14348@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOEsta dissertação apresenta uma integração entre a programação funcional e a programação em lógica, obtida pela definição e implementação da Linguagem LispLog. Nesta nova linguagem, o resultado de uma resolução pode ser utilizado como argumento de uma função (pelo operador metalisp) e o resultado da avaliação de uma função pode ser ligado a uma variável lógica (pelo operador avalia). A construção desta linguagem foi realizada a partir da simulação, em microcomputador similar ao IBM-PC, de uma máquina com arquitetura de pilhas, chamada Máquina LispLog, e de seu compilador. A utilização desta linguagem é possível através do Sistema LispLog, que fornece um ambiente de programação orientado por menus.
This dissertation shows an integration between the function programming and logic programming, achieved through LispLog Language’s definition and implementation. In this new language the resultant of a resolution may be used as an argument of a function (through metalisp operator) and the result of a function’s avaliation may be linked to a logic variable (through avalia operator). The LispLog Language was constructed by a simulation of stack architecture machine, named LispLog Machine, and its compiler, in a microcomputer similar similar to IBM-PC. The LispLog System provides a programming environment oriented by menus, wich makes possible the use of this language
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Fuller, David Alfredo. "Partial evaluation and mix computation in logic programming." Thesis, Imperial College London, 1989. http://hdl.handle.net/10044/1/47442.
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Schild, Uri Jakob. "Open-textured law, expert systems and logic programming." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/46539.
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