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Fitting free-form question-asking and spatial ability into ITS development : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Computer Science in the University of Canterbury /Milik, Nancy. January 2007 (has links)
Thesis (M. Sc.)--University of Canterbury, 2007. / Typescript (photocopy). "September 2007." Includes bibliographical references (p. 133-143). Also available via the World Wide Web.
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A study of answer set programming /Zhao, Jicheng. January 2002 (has links)
Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 49-51). Also available in electronic version. Access restricted to campus users.
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Consistency and the quantified constraint satisfaction problem /Nightingale, Peter. January 2007 (has links)
Thesis (Ph.D.) - University of St Andrews, September 2007.
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Properties of chain programs over difference contraintsArgentieri, John E. January 1900 (has links)
Thesis (M.S.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains iv, 34 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 31-34).
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Logic programming with constraintsLiu, Guohua. January 2010 (has links)
Thesis (Ph.D.)--University of Alberta, 2010. / Title from PDF file main screen (viewed on Apr. 30, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Computing Science, University of Alberta. Includes bibliographical references.
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Consistency and the Quantified Constraint Satisfaction ProblemNightingale, Peter William January 2007 (has links)
Constraint satisfaction is a very well studied and fundamental artificial intelligence technique. Various forms of knowledge can be represented with constraints, and reasoning techniques from disparate fields can be encapsulated within constraint reasoning algorithms. However, problems involving uncertainty, or which have an adversarial nature (for example, games), are difficult to express and solve in the classical constraint satisfaction problem. This thesis is concerned with an extension to the classical problem: the Quantified Constraint Satisfaction Problem (QCSP). QCSP has recently attracted interest. In QCSP, quantifiers are allowed, facilitating the expression of uncertainty. I examine whether QCSP is a useful formalism. This divides into two questions: whether QCSP can be solved efficiently; and whether realistic problems can be represented in QCSP. In attempting to answer these questions, the main contributions of this thesis are the following: - the definition of two new notions of consistency; - four new constraint propagation algorithms (with eight variants in total), along with empirical evaluations; - two novel schemes to implement the pure value rule, which is able to simplify QCSP instances; - a new optimization algorithm for QCSP; - the integration of these algorithms and techniques into a solver named Queso; - and the modelling of the Connect 4 game, and of faulty job shop scheduling, in QCSP. These are set in context by a thorough review of the QCSP literature.
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A constraint programming approach to subgraph isomorphismZampelli, Stéphane 24 June 2008 (has links)
This thesis proposes an expressive yet efficient declarative framework
for graph matching in constraint programming (CP), and focuses
on efficient algorithms to solve the subgraph isomorphism problem.
The framework is based on graph and map variables, and
specific graph morphism constraints.
This allows to model and solve various graph matching problems,
avoiding the tedious development of dedicated and specific
algorithms.
A specialized filtering algorithm is proposed for the subgraph
isomorphism problem,
which uses the semantic
of the problem as well as the global structure of the two input graphs.
It is shown that it is the state-of-the-art filtering algorithm,
compared to
dedicated algorithms and other CP approaches.
Various search techniques from CP are also extended to the subgraph
isomorphism problem.
An automatic detection and exploitation
of symmetries for the subgraph isomorphism problem is proposed, together
with
a decomposition approach of the search.
The significance of this thesis lies in the fact that, even though the
framework is expressive,
CP can be considered as the state-of-the-art for subgraph isomorphism,
outperforming the dedicated known algorithms on current benchmarks.
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Planning operations of space probes / Planning operations of space probesKolombo, Martin January 2014 (has links)
The thesis addresses a complicated real-world scheduling problem from the space operations environment. The Mars Express Orbiter scheduling problem was first presented as a challenge by the European Space Agency. The thesis compares two different solutions. The first solution is an ad-hoc scheduler that is based on scheduling actions into a set of time windows and heavily utilizes local search techniques. The second solution models the problem as a constraint satisfaction problem (CSP) and uses the SICStus Prolog constraint programming solver to find a solution. Both schedulers are experimentally evaluated and the results are compared. Both approaches were able to provide a working solution. The conclusion however states that the more generic CSP based approach was capable of producing higher quality schedules even without a complicated heuristic. It however to compute the schedule for a small subset of inputs. On the other hand, the ad-hoc scheduler was capable of solving larger inputs but the produced solutions are not as good.
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Data-parallel concurrent constraint programming.January 1994 (has links)
by Bo-ming Tong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 104-[110]). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Concurrent Constraint Programming --- p.2 / Chapter 1.2 --- Finite Domain Constraints --- p.3 / Chapter 2 --- The Firebird Language --- p.5 / Chapter 2.1 --- Finite Domain Constraints --- p.6 / Chapter 2.2 --- The Firebird Computation Model --- p.6 / Chapter 2.3 --- Miscellaneous Features --- p.7 / Chapter 2.4 --- Clause-Based N on determinism --- p.9 / Chapter 2.5 --- Programming Examples --- p.10 / Chapter 2.5.1 --- Magic Series --- p.10 / Chapter 2.5.2 --- Weak Queens --- p.14 / Chapter 3 --- Operational Semantics --- p.15 / Chapter 3.1 --- The Firebird Computation Model --- p.16 / Chapter 3.2 --- The Firebird Commit Law --- p.17 / Chapter 3.3 --- Derivation --- p.17 / Chapter 3.4 --- Correctness of Firebird Computation Model --- p.18 / Chapter 4 --- Exploitation of Data-Parallelism in Firebird --- p.24 / Chapter 4.1 --- An Illustrative Example --- p.25 / Chapter 4.2 --- Mapping Partitions to Processor Elements --- p.26 / Chapter 4.3 --- Masks --- p.27 / Chapter 4.4 --- Control Strategy --- p.27 / Chapter 4.4.1 --- A Control Strategy Suitable for Linear Equations --- p.28 / Chapter 5 --- Data-Parallel Abstract Machine --- p.30 / Chapter 5.1 --- Basic DPAM --- p.31 / Chapter 5.1.1 --- Hardware Requirements --- p.31 / Chapter 5.1.2 --- Procedure Calling Convention And Process Creation --- p.32 / Chapter 5.1.3 --- Memory Model --- p.34 / Chapter 5.1.4 --- Registers --- p.41 / Chapter 5.1.5 --- Process Management --- p.41 / Chapter 5.1.6 --- Unification --- p.49 / Chapter 5.1.7 --- Variable Table --- p.49 / Chapter 5.2 --- DPAM with Backtracking --- p.50 / Chapter 5.2.1 --- Choice Point --- p.52 / Chapter 5.2.2 --- Trailing --- p.52 / Chapter 5.2.3 --- Recovering the Process Queues --- p.57 / Chapter 6 --- Implementation --- p.58 / Chapter 6.1 --- The DECmpp Massively Parallel Computer --- p.58 / Chapter 6.2 --- Implementation Overview --- p.59 / Chapter 6.3 --- Constraints --- p.60 / Chapter 6.3.1 --- Breaking Down Equality Constraints --- p.61 / Chapter 6.3.2 --- Processing the Constraint 'As Is' --- p.62 / Chapter 6.4 --- The Wide-Tag Architecture --- p.63 / Chapter 6.5 --- Register Window --- p.64 / Chapter 6.6 --- Dereferencing --- p.65 / Chapter 6.7 --- Output --- p.66 / Chapter 6.7.1 --- Collecting the Solutions --- p.66 / Chapter 6.7.2 --- Decoding the solution --- p.68 / Chapter 7 --- Performance --- p.69 / Chapter 7.1 --- Uniprocessor Performance --- p.71 / Chapter 7.2 --- Solitary Mode --- p.73 / Chapter 7.3 --- Bit Vectors of Domain Variables --- p.75 / Chapter 7.4 --- Heap Consumption of the Heap Frame Scheme --- p.77 / Chapter 7.5 --- Eager Nondeterministic Derivation vs Lazy Nondeterministic Deriva- tion --- p.78 / Chapter 7.6 --- Priority Scheduling --- p.79 / Chapter 7.7 --- Execution Profile --- p.80 / Chapter 7.8 --- Effect of the Number of Processor Elements on Performance --- p.82 / Chapter 7.9 --- Change of the Degree of Parallelism During Execution --- p.84 / Chapter 8 --- Related Work --- p.88 / Chapter 8.1 --- Vectorization of Prolog --- p.89 / Chapter 8.2 --- Parallel Clause Matching --- p.90 / Chapter 8.3 --- Parallel Interpreter --- p.90 / Chapter 8.4 --- Bounded Quantifications --- p.91 / Chapter 8.5 --- SIMD MultiLog --- p.91 / Chapter 9 --- Conclusion --- p.93 / Chapter 9.1 --- Limitations --- p.94 / Chapter 9.1.1 --- Data-Parallel Firebird is Specialized --- p.94 / Chapter 9.1.2 --- Limitations of the Implementation Scheme --- p.95 / Chapter 9.2 --- Future Work --- p.95 / Chapter 9.2.1 --- Extending Firebird --- p.95 / Chapter 9.2.2 --- Improvements Specific to DECmpp --- p.99 / Chapter 9.2.3 --- Labeling --- p.100 / Chapter 9.2.4 --- Parallel Domain Consistency --- p.101 / Chapter 9.2.5 --- Branch and Bound Algorithm --- p.102 / Chapter 9.2.6 --- Other Possible Future Work --- p.102 / Bibliography --- p.104
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Interval linear constraint solving in constraint logic programming.January 1994 (has links)
by Chong-kan Chiu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 97-103). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Related Work --- p.2 / Chapter 1.2 --- Organizations of the Dissertation --- p.4 / Chapter 1.3 --- Notations --- p.4 / Chapter 2 --- Overview of ICLP(R) --- p.6 / Chapter 2.1 --- Basics of Interval Arithmetic --- p.6 / Chapter 2.2 --- Relational Interval Arithmetic --- p.8 / Chapter 2.2.1 --- Interval Reduction --- p.8 / Chapter 2.2.2 --- Arithmetic Primitives --- p.10 / Chapter 2.2.3 --- Interval Narrowing and Interval Splitting --- p.13 / Chapter 2.3 --- Syntax and Semantics --- p.16 / Chapter 3 --- Limitations of Interval Narrowing --- p.18 / Chapter 3.1 --- Computation Inefficiency --- p.18 / Chapter 3.2 --- Inability to Detect Inconsistency --- p.23 / Chapter 3.3 --- The Newton Language --- p.27 / Chapter 4 --- Design of CIAL --- p.30 / Chapter 4.1 --- The CIAL Architecture --- p.30 / Chapter 4.2 --- The Inference Engine --- p.31 / Chapter 4.2.1 --- Interval Variables --- p.31 / Chapter 4.2.2 --- Extended Unification Algorithm --- p.33 / Chapter 4.3 --- The Solver Interface and Constraint Decomposition --- p.34 / Chapter 4.4 --- The Linear and the Non-linear Solvers --- p.37 / Chapter 5 --- The Linear Solver --- p.40 / Chapter 5.1 --- An Interval Gaussian Elimination Solver --- p.41 / Chapter 5.1.1 --- Naive Interval Gaussian Elimination --- p.41 / Chapter 5.1.2 --- Generalized Interval Gaussian Elimination --- p.43 / Chapter 5.1.3 --- Incrementality of Generalized Gaussian Elimination --- p.47 / Chapter 5.1.4 --- Solvers Interaction --- p.50 / Chapter 5.2 --- An Interval Gauss-Seidel Solver --- p.52 / Chapter 5.2.1 --- Interval Gauss-Seidel Method --- p.52 / Chapter 5.2.2 --- Preconditioning --- p.55 / Chapter 5.2.3 --- Increment ality of Preconditioned Gauss-Seidel Method --- p.58 / Chapter 5.2.4 --- Solver Interaction --- p.71 / Chapter 5.3 --- Comparisons --- p.72 / Chapter 5.3.1 --- Time Complexity --- p.72 / Chapter 5.3.2 --- Storage Complexity --- p.73 / Chapter 5.3.3 --- Others --- p.74 / Chapter 6 --- Benchmarkings --- p.76 / Chapter 6.1 --- Mortgage --- p.78 / Chapter 6.2 --- Simple Linear Simultaneous Equations --- p.79 / Chapter 6.3 --- Analysis of DC Circuit --- p.80 / Chapter 6.4 --- Inconsistent Simultaneous Equations --- p.82 / Chapter 6.5 --- Collision Problem --- p.82 / Chapter 6.6 --- Wilkinson Polynomial --- p.85 / Chapter 6.7 --- Summary and Discussion --- p.86 / Chapter 6.8 --- Large System of Simultaneous Equations --- p.87 / Chapter 6.9 --- Comparisons Between the Incremental and the Non-Incremental Preconditioning --- p.89 / Chapter 7 --- Concluding Remarks --- p.93 / Chapter 7.1 --- Summary and Contributions --- p.93 / Chapter 7.2 --- Future Work --- p.95 / Bibliography --- p.97
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