by Lam, Hin-ki Isaac. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves 219-220). / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Problem --- p.1 / Chapter 1.2 --- Related Works --- p.3 / Chapter 1.3 --- Contribution of the Present Study --- p.8 / Chapter 1.4 --- Outline of the Thesis --- p.8 / Chapter Chapter 2 --- Nontermination and Recursive Definition --- p.11 / Chapter 2.1 --- Prolog Execution Model --- p.11 / Chapter 2.2 --- Nontermination --- p.15 / Chapter 2.3 --- Exit Condition --- p.21 / Chapter 2.4 --- Exit-Reaching Process --- p.29 / Chapter 2.5 --- Parameter Based Detection --- p.35 / Chapter Chapter 3 --- Parameter Analysis --- p.38 / Chapter 3.1 --- Parameter Links --- p.39 / Chapter 3.1.1 --- Parameter Links and Parameter Modifying Process --- p.39 / Chapter 3.1.2 --- Parameter Links of Multi-Parameters --- p.43 / Chapter 3.1.3 --- Parameter Links in Indirect Recursive Definition --- p.44 / Chapter 3.1.4 --- Parameter Links with Special Parameters --- p.46 / Chapter 3.1.5 --- Parameter Links of the Same Name Parameters --- p.47 / Chapter 3.1.6 --- The Significance of Parameter Links --- p.49 / Chapter 3.2 --- Cyclic Parameter Links --- p.51 / Chapter 3.3 --- Parameter Link Detection --- p.58 / Chapter 3.3.1 --- Graph Technique --- p.58 / Chapter 3.3.1.1 --- Preliminaries --- p.58 / Chapter 3.3.1.2 --- on Parameter Links --- p.59 / Chapter 3.3.2 --- Algorithms --- p.62 / Chapter Chapter 4 --- Data Analysis --- p.70 / Chapter 4.1 --- Data Links --- p.72 / Chapter 4.1.1 --- The Direct Recursive Definition Case --- p.76 / Chapter 4.1.1.1 --- Subgoal Procedures with Facts Alone --- p.76 / Chapter 4.1.1.2 --- Procedures with Rules --- p.79 / Chapter 4.1.2 --- The Indirect Recursive Definition Case --- p.84 / Chapter 4.2 --- on the Difference between Pure and General Prolog --- p.86 / Chapter 4.3 --- Data Link Significance --- p.89 / Chapter 4.4 --- Connected Data-link Lists --- p.92 / Chapter 4.4.1 --- Data Links and Connected Data-link Lists --- p.92 / Chapter 4.4.1.1 --- Connected Data-link Lists and Data Transfer Sequence --- p.95 / Chapter 4.4.1.2 --- Connected Data-link Lists and Backtracking --- p.97 / Chapter 4.4.1.3 --- Connected Data-link Lists and the Recursion Result --- p.99 / Chapter 4.4.2 --- Cyclic and Non-Cyclic Connected Data-link Lists --- p.100 / Chapter 4.4.2.1 --- Non-Cyclic Connected Data-link Lists and Exit Conditions --- p.102 / Chapter 4.4.2.2 --- Cyclic Connected Data-link Lists and Nontermination --- p.104 / Chapter 4.4.3 --- Multi-Connected Data-link Lists --- p.107 / Chapter 4.4.3.1 --- in One Cyclic Parameter Link --- p.107 / Chapter 4.4.3.2 --- in Multi-Cyclic Parameter Links --- p.115 / Chapter 4.4.3.3 --- The Case of Multiple Recursive Subgoals in the Same Rule --- p.120 / Chapter 4.5. --- Special Parameters and Data Links --- p.125 / Chapter 4.5.1. --- Data Links with Special Parameters Only --- p.126 / Chapter 4.5.2 --- Data Links with Both Special Parameters and Subgoals --- p.136 / Chapter 4.6 --- Data Links and Infinite Data Transfer Sequence Detection --- p.142 / Chapter CHAPTER 5 --- Special Cases --- p.150 / Chapter 5.1 --- Interdependent Cyclic Parameter Links --- p.150 / Chapter 5.1.1 --- Interdependent Cyclic Parameter Links through Common Parameters --- p.151 / Chapter 5.1.1.1 --- Interdependency between Cyclic and Non-cyclic Parameter Links and Interdependency between Cyclic Parameter Link and Subgoals --- p.158 / Chapter 5.1.1.2 --- Interdependency between Cyclic Parameter Links --- p.165 / Chapter 5.1.1.2.1 --- Lengths of Cyclic Connected- data Links in Different Ratios --- p.171 / Chapter 5.1.1.2.2 --- Cyclic Parameter Links with Lengths in Different Ratios --- p.182 / Chapter 5.1.2 --- Interdependent Cyclic Parameter Links through Common Subgoals --- p.196 / Chapter 5.1.3 --- Interdependent Cyclic Parameter Links with Special Parameters --- p.202 / Chapter 5.2 --- A Special Case of Cyclic Parameter Links established through Special Parameters --- p.208 / Chapter CHAPTER 6 --- Discussion and Conclusion --- p.213 / Chapter 6.1 --- The Results and Implications --- p.213 / Chapter 6.2 --- Limitations and Future Research --- p.215 / Chapter 6.3 --- Conclusion --- p.217 / Reference --- p.219

Chiu, Yiu Man Edmund. / Thesis submitted in: December 1999. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 269-248). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Beginning Story --- p.2 / Chapter 1.2 --- Background --- p.3 / Chapter 1.2.1 --- History of Nonmonotonic Reasoning --- p.3 / Chapter 1.2.2 --- Formalizations of Nonmonotonic Reasoning --- p.6 / Chapter 1.2.3 --- Belief Revision --- p.13 / Chapter 1.2.4 --- Network Representation of Knowledge --- p.17 / Chapter 1.2.5 --- Reference from Logic Programming --- p.21 / Chapter 1.2.6 --- Recent Work on Network-type Automatic Reasoning Sys- tems --- p.22 / Chapter 1.3 --- A Novel Inference Network Approach --- p.23 / Chapter 1.4 --- Objectives --- p.23 / Chapter 1.5 --- Organization of the Thesis --- p.24 / Chapter 2 --- The Predicate Inference Network PIN --- p.25 / Chapter 2.1 --- Preliminary Terms --- p.26 / Chapter 2.2 --- Overall Structure --- p.27 / Chapter 2.3 --- Object Layer --- p.29 / Chapter 2.3.1 --- Virtual Object --- p.31 / Chapter 2.4 --- Predicate Layer --- p.33 / Chapter 2.4.1 --- Node Values --- p.34 / Chapter 2.4.2 --- Information Source --- p.35 / Chapter 2.4.3 --- Belief State --- p.36 / Chapter 2.4.4 --- Predicates --- p.37 / Chapter 2.4.5 --- Prototypical Predicates --- p.37 / Chapter 2.4.6 --- Multiple Inputs for a Single Belief --- p.39 / Chapter 2.4.7 --- External Program Call --- p.39 / Chapter 2.5 --- Variable Layer --- p.40 / Chapter 2.6 --- Inter-Layer Links --- p.42 / Chapter 2.7 --- Chapter Summary --- p.43 / Chapter 3 --- Computation for PIN --- p.44 / Chapter 3.1 --- Computation Functions for Propagation --- p.45 / Chapter 3.1.1 --- Computational Functions for Combinative Links --- p.45 / Chapter 3.1.2 --- Computational Functions for Alternative Links --- p.49 / Chapter 3.2 --- Applying the Computation Functions --- p.52 / Chapter 3.3 --- Relations Represented in PIN --- p.55 / Chapter 3.3.1 --- Relations Represented by Combinative Links --- p.56 / Chapter 3.3.2 --- Relations Represented by Alternative Links --- p.59 / Chapter 3.4 --- Chapter Summary --- p.61 / Chapter 4 --- Dynamic Knowledge Update --- p.62 / Chapter 4.1 --- Operations for Knowledge Update --- p.63 / Chapter 4.2 --- Logical Expression --- p.63 / Chapter 4.3 --- Applicability of Operators --- p.64 / Chapter 4.4 --- Add Operation --- p.65 / Chapter 4.4.1 --- Add a fully instantiated single predicate proposition with no virtual object --- p.66 / Chapter 4.4.2 --- Add a fully instantiated pure disjunction --- p.68 / Chapter 4.4.3 --- Add a fully instantiated expression which is a conjunction --- p.71 / Chapter 4.4.4 --- Add a human biased relation --- p.74 / Chapter 4.4.5 --- Add a single predicate expression with virtual objects --- p.76 / Chapter 4.4.6 --- Add a IF-THEN rule --- p.80 / Chapter 4.5 --- Remove Operation --- p.88 / Chapter 4.5.1 --- Remove a Belief --- p.88 / Chapter 4.5.2 --- Remove a Rule --- p.91 / Chapter 4.6 --- Revise Operation --- p.94 / Chapter 4.6.1 --- Revise a Belief --- p.94 / Chapter 4.6.2 --- Revise a Rule --- p.96 / Chapter 4.7 --- Consistency Maintenance --- p.97 / Chapter 4.7.1 --- Logical Suppression --- p.98 / Chapter 4.7.2 --- Example on Handling Inconsistent Information --- p.99 / Chapter 4.8 --- Chapter Summary --- p.102 / Chapter 5 --- Knowledge Query --- p.103 / Chapter 5.1 --- Domains of Quantification --- p.104 / Chapter 5.2 --- Reasoning through Recursive Rules --- p.109 / Chapter 5.2.1 --- Infinite Looping Control --- p.110 / Chapter 5.2.2 --- Proof of the finite termination of recursive rules --- p.111 / Chapter 5.3 --- Query Functions --- p.117 / Chapter 5.4 --- Type I Queries --- p.119 / Chapter 5.4.1 --- Querying a Simple Single Predicate Proposition (Type I) --- p.122 / Chapter 5.4.2 --- Querying a Belief with Logical Connective(s) (Type I) --- p.128 / Chapter 5.5 --- Type II Queries --- p.132 / Chapter 5.5.1 --- Querying Single Predicate Expressions (Type II) --- p.134 / Chapter 5.5.2 --- Querying an Expression with Logical Connectives (Type II) --- p.143 / Chapter 5.6 --- Querying an Expression with Virtual Objects --- p.152 / Chapter 5.6.1 --- Type I Queries Involving Virtual Object --- p.152 / Chapter 5.6.2 --- Type II Queries involving Virtual Objects --- p.156 / Chapter 5.7 --- Chapter Summary --- p.157 / Chapter 6 --- Uniqueness and Finite Termination --- p.159 / Chapter 6.1 --- Proof Structure --- p.160 / Chapter 6.2 --- Proof for Completeness and Finite Termination of Domain Search- ing Procedure --- p.161 / Chapter 6.3 --- Proofs for Type I Queries --- p.167 / Chapter 6.3.1 --- Proof for Single Predicate Expressions --- p.167 / Chapter 6.3.2 --- Proof of Type I Queries on Expressions with Logical Con- nectives --- p.172 / Chapter 6.3.3 --- General Proof for Type I Queries --- p.174 / Chapter 6.4 --- Proofs for Type II Queries --- p.175 / Chapter 6.4.1 --- Proof for Type II Queries on Single Predicate Expressions --- p.176 / Chapter 6.4.2 --- Proof for Type II Queries on Disjunctions --- p.178 / Chapter 6.4.3 --- Proof for Type II Queries on Conjunctions --- p.179 / Chapter 6.4.4 --- General Proof for Type II Queries --- p.181 / Chapter 6.5 --- Proof for Queries Involving Virtual Objects --- p.182 / Chapter 6.6 --- Uniqueness and Finite Termination of PIN Queries --- p.183 / Chapter 6.7 --- Chapter Summary --- p.184 / Chapter 7 --- Lifschitz's Benchmark Problems --- p.185 / Chapter 7.1 --- Structure --- p.186 / Chapter 7.2 --- Default Reasoning --- p.186 / Chapter 7.2.1 --- Basic Default Reasoning --- p.186 / Chapter 7.2.2 --- Default Reasoning with Irrelevant Information --- p.187 / Chapter 7.2.3 --- Default Reasoning with Several Defaults --- p.188 / Chapter 7.2.4 --- Default Reasoning with a Disabled Default --- p.190 / Chapter 7.2.5 --- Default Reasoning in Open Domain --- p.191 / Chapter 7.2.6 --- Reasoning about Unknown Exceptions I --- p.193 / Chapter 7.2.7 --- Reasoning about Unknown Exceptions II --- p.194 / Chapter 7.2.8 --- Reasoning about Unknown Exceptions III --- p.196 / Chapter 7.2.9 --- Priorities between Defaults --- p.198 / Chapter 7.2.10 --- Priorities between Instances of a Default --- p.199 / Chapter 7.2.11 --- Reasoning about Priorities --- p.199 / Chapter 7.3 --- Inheritance --- p.200 / Chapter 7.3.1 --- Linear Inheritance --- p.200 / Chapter 7.3.2 --- Tree-Structured Inheritance --- p.202 / Chapter 7.3.3 --- One-Step Multiple Inheritance --- p.203 / Chapter 7.3.4 --- Multiple Inheritance --- p.204 / Chapter 7.4 --- Uniqueness of Names --- p.205 / Chapter 7.4.1 --- Unique Names Hypothesis for Objects --- p.205 / Chapter 7.4.2 --- Unique Names Hypothesis for Functions --- p.206 / Chapter 7.5 --- Reasoning about Action --- p.206 / Chapter 7.6 --- Autoepistemic Reasoning --- p.206 / Chapter 7.6.1 --- Basic Autoepistemic Reasoning --- p.206 / Chapter 7.6.2 --- Autoepistemic Reasoning with Incomplete Information --- p.207 / Chapter 7.6.3 --- Autoepistemic Reasoning with Open Domain --- p.207 / Chapter 7.6.4 --- Autoepistemic Default Reasoning --- p.208 / Chapter 8 --- Comparison with PROLOG --- p.214 / Chapter 8.1 --- Introduction of PROLOG --- p.215 / Chapter 8.1.1 --- Brief History --- p.215 / Chapter 8.1.2 --- Structure and Inference --- p.215 / Chapter 8.1.3 --- Why Compare PIN with Prolog --- p.216 / Chapter 8.2 --- Representation Power --- p.216 / Chapter 8.2.1 --- Close World Assumption and Negation as Failure --- p.216 / Chapter 8.2.2 --- Horn Clauses --- p.217 / Chapter 8.2.3 --- Quantification --- p.218 / Chapter 8.2.4 --- Build-in Functions --- p.219 / Chapter 8.2.5 --- Other Representation Issues --- p.220 / Chapter 8.3 --- Inference and Query Processing --- p.220 / Chapter 8.3.1 --- Unification --- p.221 / Chapter 8.3.2 --- Resolution --- p.222 / Chapter 8.3.3 --- Computation Efficiency --- p.225 / Chapter 8.4 --- Knowledge Updating and Consistency Issues --- p.227 / Chapter 8.4.1 --- PIN and AGM Logic --- p.228 / Chapter 8.4.2 --- Knowledge Merging --- p.229 / Chapter 8.5 --- Chapter Summary --- p.229 / Chapter 9 --- Conclusion and Discussion --- p.230 / Chapter 9.1 --- Conclusion --- p.231 / Chapter 9.1.1 --- General Structure --- p.231 / Chapter 9.1.2 --- Representation Power --- p.231 / Chapter 9.1.3 --- Inference --- p.232 / Chapter 9.1.4 --- Dynamic Update and Consistency --- p.233 / Chapter 9.1.5 --- Soundness and Completeness Versus Efficiency --- p.233 / Chapter 9.2 --- Discussion --- p.234 / Chapter 9.2.1 --- Different Selection Criteria --- p.234 / Chapter 9.2.2 --- Link Order --- p.235 / Chapter 9.2.3 --- Inheritance Reasoning --- p.236 / Chapter 9.3 --- Future Work --- p.237 / Chapter 9.3.1 --- Implementation --- p.237 / Chapter 9.3.2 --- Application --- p.237 / Chapter 9.3.3 --- Probabilistic and Fuzzy PIN --- p.238 / Chapter 9.3.4 --- Temporal Reasoning --- p.238 / Bibliography --- p.239

Logic programming languages have generated increasing interest over the last few years. Logic programming languages like Prolog are being explored for different applications. Prolog is inherently parallel. Attempts are being made to utilize this inherent parallelism. There are two kinds of parallelism present in Prolog, OR parallelism and AND parallelism. OR parallelism is relatively easy to exploit while AND parallelism poses interesting issues. One of the main issues is dependencies between literals. It is very important to use the AND parallelism available in the language structure as not exploiting it would result in a substantial loss of parallelism. Any system trying to make use of either or both kinds of parallelism would need to have the capability of performing faster unification, as it affects the overall execution time greatly. A new architecture design is presented in this thesis that exploits both kinds of parallelism. The architecture efficiently implements some of the key concepts in Conery's approach to parallel execution [5]. The architecture has a memory hierarchy that uses associative memory. Associative memories are useful for faster lookup and response and hence their use results in quick response time. Along with the use of a memory hierarchy, execution algorithms and rules for ordering of literals are presented. The rules for ordering of literals are helpful in determining the order of execution. The analysis of response time is done for different configurations of the architecture, from sequential execution with one processor to multiple processing units having multiple processors. A benchmark program, "query," is used for obtaining results, and the map coloring problem is also solved on different configurations and results are compared. To obtain results the goals and subgoals are assigned to different processors by creating a tree. These assignments and transferring of goals are simulated by hand. The total time includes the time needed for moving goals back and forth from one processor to another. The total time is calculated in number of cycles with some assumptions about memory response time, communication time, number of messages that can be sent on the bus at a particular instant, etc. The results obtained show that the architecture efficiently exploits the AND parallelism and OR parallelism available in Prolog. The total time needed for different configurations is then compared and conclusions are drawn.

No description available.

The purpose of this study is to explore that mathematics provides a convenient formalism for studying classical database management system problems. There are two main parts in this study, devoted respectively to using mathematical theory of relations and using logical theory to study database management systems. In the first part we focus on relational model and relational algebra. The second part deals with the application of mathematical logic to database management systems, where logic may be used both as a inference system and as a representation language. The features and logical mechanisms of Prolog programming language have been studied. A sample logical database model is developed and tested, using the logic programming language Prolog. / Department of Computer Science

Computers are used for diagnostic and training in the neuropsychological rehabilitation. PLANTEST is a program for the IBM-PC that was developed for diagnostic support. It implements a test that gives information about the reduced ability of brain-injured patients to make plans regarding a certain task.The presented thesis describes a knowledge-based system that can be used to develop new test versions for PLANTEST. The program is called SolvePT and it can prove the solubility of test material used in PLANTEST. It can also automatically generate new test material. The program uses an exhaustive forward-chaining, depth-first search and is implemented in Prolog. The datastructures and algorithm of the program as well as space and time requirements are discussed. / Department of Computer Science

This thesis creates an small expert system that is based on Einstein's special relativity. The basic knowledge of special relativity and the bases for building an expert system are described. The concepts of special relativity are put into a knowledge base by changing the formulas into rules and facts. The Prolog language was used to develop the expert system. New information can be input that does not contradict the rules and facts already in the database. The system also uses computer graphics to demonstrate the physical concepts of relativity. By using this expert system, one can teach the basic knowledge of special relativity and solve some problems related to frames of reference moving with high speed. / Department of Computer Science

Thesis (M.S.)--University of Texas at El Paso, 2007. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.S.)--Rochester Institute of Technology, 1987. / Typescript. Includes bibliographical references (leaves viii-xi).

Thesis (M.S.)--Rochester Institute of Technology, 1994. / Typescript. Includes bibliographical references (leaf 217).