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We present an algebraic view on logic programming, related to proof theory and more specifically linear logic and geometry of interaction. Within this construction, a characterization of logspace (deterministic and non-deterministic) computation is given via a synctactic restriction, using an encoding of words that derives from proof theory. We show that the acceptance of a word by an observation (the counterpart of a program in the encoding) can be decided within logarithmic space, by reducing this problem to the acyclicity of a graph. We show moreover that observations are as expressive as two-ways multi-heads finite automata, a kind of pointer machines that is a standard model of logarithmic space computation.

45 p. 28 cm

6800 Programming for Logic Design By Adam Osborne Copyright 1977 This description contains and overview of the book, a list of the table of contents and a review of the book by Jeff Grossman from The Best of Creative Computing, Volume 3. Introduction This book explains how an assembly language program within a microcomputer system can replace combinational logic- that is, the combined use of "off-the-shelf," non-programmable logic devices, such as standard 7400 series digital logic. If you are a logic designer, this book will teach you how to do your old job in a new way- by creating assembly language programs within a microcomputer system. If you are a programmer, this book will show you how programming has found a new purpose- in logic design. This is a "how to do it" book; as such, it has to become very specific, so a particular type of microcomputer, the MC6800, is referenced directly. Companies manufacturing these microcomputers are: Motorola. Incorporated Semiconductor Products Division 3501 Ed Bluestein Boulevard Austin, Texas 78721 American Microsystems 3800 Homestead Road Santa Clara, California 95051 What This Book Assumes You Know This book is a sequel to An Introduction To Microcomputers , which was a single volume in its first edition, but is two volumes in its second edition. An Introduction To Microcomputers describes microprocessors and microcomputers conceptually; it does not address itself to the practical matter of implementing a concept. This book addresses the practical matter of implementation. In that this book is a sequel, it makes a single assumption- that you have read, or you otherwise understand the material covered in An Introduction To Microcomputers. However, before launching into a real design project, you will need vendor literature that specifically describes the devices you have elected to use. Note in particular that hardware and timing are not described in this book, either for the MC6800 CPU, or any other microcomputer devices; sufficient information may be found in An Introduction To Microcomputers, Volume II- Some Real Products. The MC6800 instruction set is described in Chapter 6 of this book, since programming is what this book is all about. Understanding Assembly Language Assembly language instructions are the transfer functions of a microcomputer system; taken together, they constitute an "instruction set," which describes the individual operations which the microcomputer can perform. You define the events which must occur within the microcomputer system serially- as a sequence of instructions, which, taken together, constitute an assembly language program. In reality, understanding what individual instructions do within a microcomputer system is very straightforward; it is one of the simplest aspects of working with microcomputers. Yet it unduly terrifies users who are new to programming. If that includes you, a word of advice - forget about mnemonics and instruction sets; take instructions one at a time as you encounter them in this book. When you do not understand what an instruction is doing, look it up in Chapter 6. The specter of "programming" will haunt you only if you let it. How This Book Has Been Printed Notice that text in this book has been printed in boldface type and lightface type. This has been done to help you skip those parts of the book that cover subject matter with which you are familiar. You can be sure that lightface type only expands on information presented in the previous boldface type. Therefore, only read boldface type until you reach a subject about which you want to know more, at which point start reading the lightface type. Table of Contents 1) Introduction 2) Assembly Language and Digital Logic 3) A Direct Digital Logic Simulation 4) A Simple Program 5) A Programmer's Perspective 6) The MC6800 Instruction Set 7) Some Commonly Used Routines Review of 6800 Programming for Logic Design by Adam Osborne Review by Jeff Grossman This review was published in the 1980 book, The Best of Creative Computing, Volume 3 on page 305.   6800 Programming for Logic Design. Adam Osborne. Adam Osborne and Associates, Inc. 289 pp., paperback. $7.50, 1977. With all the largely worthless books being published about microprocessors and microcomputers, it is refreshing to find one that sets its goals short of solving all the world's problems, and then meets these goals with a clarity, conciseness, and competence not often found in other books on the same subject. Author Osborne's intent is to show how assembly-language programs, in microprocessors, can replace discrete logic components. This is explained in the context of the Motorola 6800, but is applicable to almost any microprocessor. In seven chapters, the last two of which are 6800 reference material, the reader is guided from software simulation of gates to digital-system implementation via programming. Osborne begins by showing how simple gates and flip-flops can be replaced by small segments of assembly-language code.  He then points out that using a microprocessor to replace a gate or a flip-flop is wasteful, and presents an example of replacing an entire circuit with a microprocessor.  The circuit, used throughout the book, is an excellent vehicle for getting concepts across.  The circuit is taken from an actual product, the Qume daisy-wheel printer, and provides a mixture of synchronization, timing delay, and control problems that manages to illustrate most of the major issues in this type of design.  Again the reader is told that all is not perfect.  The assembly-language program, while functionally correct, is really a direct gate and flip-flop emulation of the print-wheel and hammer-control circuit.  This is generally not the best approach as such a direct simulation of a working digital circuit may not work due to unsuspected timing dependencies, lack of parallelism, etc.  The circuit is then re-implemented, ignoring the gates and, instead of concentrating on providing the functionality of the original circuit and preserving its input/output relationship.  But the author is not finished yet.  He describes a third, and final, program with some optimizations revealed by examining the problem from a software viewpoint. A unique feature of this book is that it is printed in boldface and lightface type.  The boldface type (more sparse) presents the key ideas, while the lightface type expands upon them.  Thus the reader can skip the detailed explanations when not required, but, upon reaching an unfamiliar topic, will find sufficient detail to answer most questions.  The only criticism is that the diagrams tend to be somewhat cluttered.  Particularly annoying is the practice of drawing arrows directly on assembly-language and diagram text to illustrate a point.  This, however, is a minor problem in an otherwise fine book. The author assumes a knowledge of basic microprocessor principles.  In practice, someone with a background in elementary combinational and sequential circuits and some form of programming will be able to benefit from this book.  6800 Programming for Logic Design is not for those who get their thrills by playing Spacewar, but anyone who designs microprocessor systems, or who is interested in doing so, will find this book interesting, informative, and useful. Jeff Grossman Cambridge,MA

6800 Programming for Logic Design By Adam Osborne Copyright 1977 This description contains and overview of the book, a list of the table of contents and a review of the book by Jeff Grossman from The Best of Creative Computing, Volume 3. Introduction This book explains how an assembly language program within a microcomputer system can replace combinational logic- that is, the combined use of "off-the-shelf," non-programmable logic devices, such as standard 7400 series digital logic. If you are a logic designer, this book will teach you how to do your old job in a new way- by creating assembly language programs within a microcomputer system. If you are a programmer, this book will show you how programming has found a new purpose- in logic design. This is a "how to do it" book; as such, it has to become very specific, so a particular type of microcomputer, the MC6800, is referenced directly. Companies manufacturing these microcomputers are: Motorola. Incorporated Semiconductor Products Division 3501 Ed Bluestein Boulevard Austin, Texas 78721 American Microsystems 3800 Homestead Road Santa Clara, California 95051 What This Book Assumes You Know This book is a sequel to An Introduction To Microcomputers , which was a single volume in its first edition, but is two volumes in its second edition. An Introduction To Microcomputers describes microprocessors and microcomputers conceptually; it does not address itself to the practical matter of implementing a concept. This book addresses the practical matter of implementation. In that this book is a sequel, it makes a single assumption- that you have read, or you otherwise understand the material covered in An Introduction To Microcomputers. However, before launching into a real design project, you will need vendor literature that specifically describes the devices you have elected to use. Note in particular that hardware and timing are not described in this book, either for the MC6800 CPU, or any other microcomputer devices; sufficient information may be found in An Introduction To Microcomputers, Volume II- Some Real Products. The MC6800 instruction set is described in Chapter 6 of this book, since programming is what this book is all about. Understanding Assembly Language Assembly language instructions are the transfer functions of a microcomputer system; taken together, they constitute an "instruction set," which describes the individual operations which the microcomputer can perform. You define the events which must occur within the microcomputer system serially- as a sequence of instructions, which, taken together, constitute an assembly language program. In reality, understanding what individual instructions do within a microcomputer system is very straightforward; it is one of the simplest aspects of working with microcomputers. Yet it unduly terrifies users who are new to programming. If that includes you, a word of advice - forget about mnemonics and instruction sets; take instructions one at a time as you encounter them in this book. When you do not understand what an instruction is doing, look it up in Chapter 6. The specter of "programming" will haunt you only if you let it. How This Book Has Been Printed Notice that text in this book has been printed in boldface type and lightface type. This has been done to help you skip those parts of the book that cover subject matter with which you are familiar. You can be sure that lightface type only expands on information presented in the previous boldface type. Therefore, only read boldface type until you reach a subject about which you want to know more, at which point start reading the lightface type. Table of Contents 1) Introduction 2) Assembly Language and Digital Logic 3) A Direct Digital Logic Simulation 4) A Simple Program 5) A Programmer's Perspective 6) The MC6800 Instruction Set 7) Some Commonly Used Routines Review of 6800 Programming for Logic Design by Adam Osborne Review by Jeff Grossman This review was published in the 1980 book, The Best of Creative Computing, Volume 3 on page 305.   6800 Programming for Logic Design. Adam Osborne. Adam Osborne and Associates, Inc. 289 pp., paperback. $7.50, 1977. With all the largely worthless books being published about microprocessors and microcomputers, it is refreshing to find one that sets its goals short of solving all the world's problems, and then meets these goals with a clarity, conciseness, and competence not often found in other books on the same subject. Author Osborne's intent is to show how assembly-language programs, in microprocessors, can replace discrete logic components. This is explained in the context of the Motorola 6800, but is applicable to almost any microprocessor. In seven chapters, the last two of which are 6800 reference material, the reader is guided from software simulation of gates to digital-system implementation via programming. Osborne begins by showing how simple gates and flip-flops can be replaced by small segments of assembly-language code.  He then points out that using a microprocessor to replace a gate or a flip-flop is wasteful, and presents an example of replacing an entire circuit with a microprocessor.  The circuit, used throughout the book, is an excellent vehicle for getting concepts across.  The circuit is taken from an actual product, the Qume daisy-wheel printer, and provides a mixture of synchronization, timing delay, and control problems that manages to illustrate most of the major issues in this type of design.  Again the reader is told that all is not perfect.  The assembly-language program, while functionally correct, is really a direct gate and flip-flop emulation of the print-wheel and hammer-control circuit.  This is generally not the best approach as such a direct simulation of a working digital circuit may not work due to unsuspected timing dependencies, lack of parallelism, etc.  The circuit is then re-implemented, ignoring the gates and, instead of concentrating on providing the functionality of the original circuit and preserving its input/output relationship.  But the author is not finished yet.  He describes a third, and final, program with some optimizations revealed by examining the problem from a software viewpoint. A unique feature of this book is that it is printed in boldface and lightface type.  The boldface type (more sparse) presents the key ideas, while the lightface type expands upon them.  Thus the reader can skip the detailed explanations when not required, but, upon reaching an unfamiliar topic, will find sufficient detail to answer most questions.  The only criticism is that the diagrams tend to be somewhat cluttered.  Particularly annoying is the practice of drawing arrows directly on assembly-language and diagram text to illustrate a point.  This, however, is a minor problem in an otherwise fine book. The author assumes a knowledge of basic microprocessor principles.  In practice, someone with a background in elementary combinational and sequential circuits and some form of programming will be able to benefit from this book.  6800 Programming for Logic Design is not for those who get their thrills by playing Spacewar, but anyone who designs microprocessor systems, or who is interested in doing so, will find this book interesting, informative, and useful. Jeff Grossman Cambridge,MA

The Journal of Logic Programming 1985: Volume 2 , Issue CONTENTS. Digitized from IA1652909-07 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1985_2_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1985-04_2_1 .

TU Dresden CMS LM Foundations of Logic Programming Exam 2021-2022

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The Journal of Logic Programming 1991: Volume 10 , Issue Index. Digitized from IA1652909-07 . Previous issue: sim_journal-of-logic-and-algebraic-programming_september-november-1990_9_2-3 . Next issue: sim_journal-of-logic-and-algebraic-programming_1991_10_contents .

The aim of the Alma project is the design of a strongly typed constraint programming language that combines the advantages of logic and imperative programming. The first stage of the project was the design and implementation of Alma-0, a small programming language that provides a support for declarative programming within the imperative programming framework. It is obtained by extending a subset of Modula-2 by a small number of features inspired by the logic programming paradigm. In this paper we discuss the rationale for the design of Alma-0, the benefits of the resulting hybrid programming framework, and the current work on adding constraint processing capabilities to the language. In particular, we discuss the role of the logical and customary variables, the interaction between the constraint store and the program, and the need for lists.

The aim of the Alma project is the design of a strongly typed constraint programming language that combines the advantages of logic and imperative programming. The first stage of the project was the design and implementation of Alma-0, a small programming language that provides a support for declarative programming within the imperative programming framework. It is obtained by extending a subset of Modula-2 by a small number of features inspired by the logic programming paradigm. In this paper we discuss the rationale for the design of Alma-0, the benefits of the resulting hybrid programming framework, and the current work on adding constraint processing capabilities to the language. In particular, we discuss the role of the logical and customary variables, the interaction between the constraint store and the program, and the need for lists.

We study conditions for a concurrent construction of proof-nets in the framework developed by Andreoli in recent papers. We define specific correctness criteria for that purpose. We first study closed modules (i.e. validity of the execution of a logic program), then extend the criterion to open modules (i.e. validity during the execution) distinguishing criteria for acyclicity and connectability in order to allow incremental verification.

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. The core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. The core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. The core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given queries being true provided a set of mutually independent random variables, a model (a logic program) and some evidence. The core of solving this inference task involves translating the logic program to a propositional theory and using a model counter. In this paper, we show that for some problems that involve inductive definitions like reachability in a graph, the translation of logic programs to SAT can be expensive for the purpose of solving inference tasks. For such problems, direct implementation of stable model semantics allows for more efficient solving. We present two implementation techniques, based on unfounded set detection, that extend a propositional model counter to a stable model counter. Our experiments show that for particular problems, our approach can outperform a state-of-the-art probabilistic logic programming solver by several orders of magnitude in terms of running time and space requirements, and can solve instances of significantly larger sizes on which the current solver runs out of time or memory.

The Journal of Logic and Algebraic Programming 1999: Volume 39 , Issue Index. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1999-03_38_3 . Next issue: sim_journal-of-logic-and-algebraic-programming_1999_39_contents . Note: This issue has no cover

The Journal of Logic and Algebraic Programming 1999: Volume 39 , Issue Index. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1999-03_38_3 . Next issue: sim_journal-of-logic-and-algebraic-programming_1999_39_contents . Note: This issue has no cover

Includes bibliographies and index

Includes bibliographies and index

Includes bibliographies and index

Includes bibliographies and index

The focus of this work was to study large volatile knowledge bases. The research involved developing extensions to logic programming systems in the form of a metalanguage, by studying to what extent frames and semantic nets could be employed. The management of consistency and integrity under change using a metalanguage was analyzed. This research produced a rule-based deductive programming language, called metaProglog, which enhances Prolog's ability to manipulate the databases themselves and to reason about them. This was accomplished by regarding databases (or theories) as first-class objects capable of being passed as arguments. Four papers were published under this grant, including Meta-kavek programming and knowledge representation and metaProlog: A metalevel extension to Prolog. (Author)

The focus of this work was to study large volatile knowledge bases. The research involved developing extensions to logic programming systems in the form of a metalanguage, by studying to what extent frames and semantic nets could be employed. The management of consistency and integrity under change using a metalanguage was analyzed. This research produced a rule-based deductive programming language, called metaProglog, which enhances Prolog's ability to manipulate the databases themselves and to reason about them. This was accomplished by regarding databases (or theories) as first-class objects capable of being passed as arguments. Four papers were published under this grant, including Meta-kavek programming and knowledge representation and metaProlog: A metalevel extension to Prolog. (Author)

This paper uses logic programming to describe numerical integration in a general way. Axioms are added to the basic logic programs to define specific known numerical integration algorithms. Using a slightly different formalization, we construct logic programs for adaptive Romberg integration and for a new algorithm for adaptive integration. The logic programs provide a formal basis for classifying numerical quadrature algorithms (recall Rice's comment that there are 1,000,000 useful ones). The logic programs are also more understandable than the corresponding programs in conventional programming languages. In terms of logic programming there are several novel points in this paper. The data type, real number, is not definded by a recursive constructor function. Termination is decided by error bounds, rather than by reaching some basis case of the data constructor. The problem itself seems to demand concurrent execution and global variables but in fact is solved in a linear fashion. (Author)

During this period, the investigator intended to investigate alternative approaches for improving searching performance in logic programming systems to a level that would be acceptable in a production system by conducting experiments in the LOGLISP system. Due to incompatibilities between the DEC 10 source computer and the CDC CYBER 760 running under NOS, which was available at Florida State University, as well as the differences between the UCI LISP on the DEC 10 and the ALISP available on the CYBER, it was impossible to bring the LOGLISP system to fully operational status and perform the experiments. (Author)

Reasoning about complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we present the MANCaLog language, a formalism based on logic programming that satisfies a set of desiderata proposed in previous work as recommendations for the development of approaches to reasoning in complex networks. To the best of our knowledge, this is the first formalism that satisfies all such criteria. We first focus on algorithms for finding minimal models (on which multi-attribute analysis can be done), and then on how this formalism can be applied in certain real world scenarios. Towards this end, we study the problem of deciding group membership in social networks: given a social network and a set of groups where group membership of only some of the individuals in the network is known, we wish to determine a degree of membership for the remaining group-individual pairs. We develop a prototype implementation that we use to obtain experimental results on two real world datasets, including a current social network of criminal gangs in a major U.S. city. We then show how the assignment of degree of membership to nodes in this case allows for a better understanding of the criminal gang problem when combined with other social network mining techniques including detection of sub-groups and identification of core group memberswhich would not be possible without further identification of additional group members.

Reasoning about complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we present the MANCaLog language, a formalism based on logic programming that satisfies a set of desiderata proposed in previous work as recommendations for the development of approaches to reasoning in complex networks. To the best of our knowledge, this is the first formalism that satisfies all such criteria. We first focus on algorithms for finding minimal models (on which multi-attribute analysis can be done), and then on how this formalism can be applied in certain real world scenarios. Towards this end, we study the problem of deciding group membership in social networks: given a social network and a set of groups where group membership of only some of the individuals in the network is known, we wish to determine a degree of membership for the remaining group-individual pairs. We develop a prototype implementation that we use to obtain experimental results on two real world datasets, including a current social network of criminal gangs in a major U.S. city. We then show how the assignment of degree of membership to nodes in this case allows for a better understanding of the criminal gang problem when combined with other social network mining techniques including detection of sub-groups and identification of core group memberswhich would not be possible without further identification of additional group members.

Reasoning about complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we present the MANCaLog language, a formalism based on logic programming that satisfies a set of desiderata proposed in previous work as recommendations for the development of approaches to reasoning in complex networks. To the best of our knowledge, this is the first formalism that satisfies all such criteria. We first focus on algorithms for finding minimal models (on which multi-attribute analysis can be done), and then on how this formalism can be applied in certain real world scenarios. Towards this end, we study the problem of deciding group membership in social networks: given a social network and a set of groups where group membership of only some of the individuals in the network is known, we wish to determine a degree of membership for the remaining group-individual pairs. We develop a prototype implementation that we use to obtain experimental results on two real world datasets, including a current social network of criminal gangs in a major U.S. city. We then show how the assignment of degree of membership to nodes in this case allows for a better understanding of the criminal gang problem when combined with other social network mining techniques including detection of sub-groups and identification of core group memberswhich would not be possible without further identification of additional group members.

Reasoning about complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we present the MANCaLog language, a formalism based on logic programming that satisfies a set of desiderata proposed in previous work as recommendations for the development of approaches to reasoning in complex networks. To the best of our knowledge, this is the first formalism that satisfies all such criteria. We first focus on algorithms for finding minimal models (on which multi-attribute analysis can be done), and then on how this formalism can be applied in certain real world scenarios. Towards this end, we study the problem of deciding group membership in social networks: given a social network and a set of groups where group membership of only some of the individuals in the network is known, we wish to determine a degree of membership for the remaining group-individual pairs. We develop a prototype implementation that we use to obtain experimental results on two real world datasets, including a current social network of criminal gangs in a major U.S. city. We then show how the assignment of degree of membership to nodes in this case allows for a better understanding of the criminal gang problem when combined with other social network mining techniques including detection of sub-groups and identification of core group memberswhich would not be possible without further identification of additional group members.

Reasoning about complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we present the MANCaLog language, a formalism based on logic programming that satisfies a set of desiderata proposed in previous work as recommendations for the development of approaches to reasoning in complex networks. To the best of our knowledge, this is the first formalism that satisfies all such criteria. We first focus on algorithms for finding minimal models (on which multi-attribute analysis can be done), and then on how this formalism can be applied in certain real world scenarios. Towards this end, we study the problem of deciding group membership in social networks: given a social network and a set of groups where group membership of only some of the individuals in the network is known, we wish to determine a degree of membership for the remaining group-individual pairs. We develop a prototype implementation that we use to obtain experimental results on two real world datasets, including a current social network of criminal gangs in a major U.S. city. We then show how the assignment of degree of membership to nodes in this case allows for a better understanding of the criminal gang problem when combined with other social network mining techniques including detection of sub-groups and identification of core group memberswhich would not be possible without further identification of additional group members.

CS 61A The Structure and Interpretation of Computer Programs Instructor Brian Harvey Spring 2008 Introduction to programming and computer science. This course exposes students to techniques of abstraction at several levels: (a) within a programming language, using higher-order functions, manifest types, data-directed programming, and message-passing; (b) between programming languages, using functional and rule-based languages as examples. It also relates these techniques to the practical problems of implementation of languages and algorithms on a von Neumann machine. There are several significant programming projects, programmed in a dialect of the LISP language.

In designing the interface between a database and a logic system with inference such as Prolog, efficiency is the major issue. Presented here are three of the methods that are considered most promising and in which much research is focused. The first method explores extending an inference machine to include a database manager, the second couples the inference mechanism with a database management system; and the third extends a database management mechanism to include inference. Acknowledging up front that no method can be claimed best, the major emphasis of this study will be to determine the strengths and limitations of all three methods and thereby help to clarify many uncertain and sometimes conflicting issues caused by the parallel lines of development from the database and artificial intelligence communities.

Functional and Logic Programming: 5th International Symposium, FLOPS 2001 Tokyo, Japan, March 7–9, 2001 Proceedings Author: Herbert Kuchen, Kazunori Ueda Published by Springer Berlin Heidelberg ISBN: 978-3-540-41739-2 DOI: 10.1007/3-540-44716-4 Table of Contents: The Metalanguage λprolog and Its Implementation A Scalable Architecture for Proof-Carrying Code Parameterized Logic Programs where Computing Meets Learning Proving Syntactic Properties of Exceptions in an Ordered Logical Framework A Higher-Order Colon Translation Compiling Lazy Functional Programs Based on the Spineless Tagless G-machine for the Java Virtual Machine A Higher-Order Logic Programming Language with Constraints Specifying and Debugging Security Protocols via Hereditary Harrop Formulas and λProlog ‐ A Case-study ‐ An Effective Bottom-Up Semantics for First-Order Linear Logic Programs A Framework for Goal-Directed Bottom-Up Evaluation of Functional Logic Programs Theoretical Foundations for the Declarative Debugging of Lazy Functional Logic Programs Adding Linear Constraints over Real Numbers to Curry A Complete Selection Function for Lazy Conditional Narrowing An Abstract Machine Based System for a Lazy Narrowing Calculus Incremental Learning of Functional Logic Programs A General Type Inference Framework for Hindley/Milner Style Systems Monadic Encapsulation with Stack of Regions Well-Typed Logic Programs Are not Wrong A Framework for Analysis of Typed Logic Programs Abstract Compilation for Sharing Analysis

Functional and Logic Programming: 5th International Symposium, FLOPS 2001 Tokyo, Japan, March 7–9, 2001 Proceedings Author: Herbert Kuchen, Kazunori Ueda Published by Springer Berlin Heidelberg ISBN: 978-3-540-41739-2 DOI: 10.1007/3-540-44716-4 Table of Contents: The Metalanguage λprolog and Its Implementation A Scalable Architecture for Proof-Carrying Code Parameterized Logic Programs where Computing Meets Learning Proving Syntactic Properties of Exceptions in an Ordered Logical Framework A Higher-Order Colon Translation Compiling Lazy Functional Programs Based on the Spineless Tagless G-machine for the Java Virtual Machine A Higher-Order Logic Programming Language with Constraints Specifying and Debugging Security Protocols via Hereditary Harrop Formulas and λProlog ‐ A Case-study ‐ An Effective Bottom-Up Semantics for First-Order Linear Logic Programs A Framework for Goal-Directed Bottom-Up Evaluation of Functional Logic Programs Theoretical Foundations for the Declarative Debugging of Lazy Functional Logic Programs Adding Linear Constraints over Real Numbers to Curry A Complete Selection Function for Lazy Conditional Narrowing An Abstract Machine Based System for a Lazy Narrowing Calculus Incremental Learning of Functional Logic Programs A General Type Inference Framework for Hindley/Milner Style Systems Monadic Encapsulation with Stack of Regions Well-Typed Logic Programs Are not Wrong A Framework for Analysis of Typed Logic Programs Abstract Compilation for Sharing Analysis

Functional and Logic Programming: 5th International Symposium, FLOPS 2001 Tokyo, Japan, March 7–9, 2001 Proceedings Author: Herbert Kuchen, Kazunori Ueda Published by Springer Berlin Heidelberg ISBN: 978-3-540-41739-2 DOI: 10.1007/3-540-44716-4 Table of Contents: The Metalanguage λprolog and Its Implementation A Scalable Architecture for Proof-Carrying Code Parameterized Logic Programs where Computing Meets Learning Proving Syntactic Properties of Exceptions in an Ordered Logical Framework A Higher-Order Colon Translation Compiling Lazy Functional Programs Based on the Spineless Tagless G-machine for the Java Virtual Machine A Higher-Order Logic Programming Language with Constraints Specifying and Debugging Security Protocols via Hereditary Harrop Formulas and λProlog ‐ A Case-study ‐ An Effective Bottom-Up Semantics for First-Order Linear Logic Programs A Framework for Goal-Directed Bottom-Up Evaluation of Functional Logic Programs Theoretical Foundations for the Declarative Debugging of Lazy Functional Logic Programs Adding Linear Constraints over Real Numbers to Curry A Complete Selection Function for Lazy Conditional Narrowing An Abstract Machine Based System for a Lazy Narrowing Calculus Incremental Learning of Functional Logic Programs A General Type Inference Framework for Hindley/Milner Style Systems Monadic Encapsulation with Stack of Regions Well-Typed Logic Programs Are not Wrong A Framework for Analysis of Typed Logic Programs Abstract Compilation for Sharing Analysis

The Journal of Logic Programming 1987: Volume 4 , Issue Index. Digitized from IA1652909-07 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1986-12_3_4 . Next issue: sim_journal-of-logic-and-algebraic-programming_1987_4_contents .

The Journal of Logic and Algebraic Programming 1996: Volume 28 , Issue CONTENTS. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1996_28_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1996-07_28_1 . Note: This issue has no cover

"Algernon: An Introduction to Programming Logic" is a 1987 educational game designed by Tom Bretl, programmed by Larry Bank, and distributed by Sunburst Communications. It requires a 64K Apple ][+ or later.

"Algernon: An Introduction to Programming Logic" is a 1987 educational game designed by Tom Bretl, programmed by Larry Bank, and distributed by Sunburst Communications. It requires a 64K Apple ][+ or later.

TU Dresden CMS LM Foundations of Logic Programming Exam 2022-2023

TU Dresden CMS LM Foundations of Logic Programming Exam 2022-2023

xvi, 367 pages : 24 cm

xvi, 367 pages : 24 cm

The Journal of Logic Programming 1988: Volume 5 , Issue CONTENTS. Digitized from IA1652909-07 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1988_5_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1988-03_5_1 .

The Journal of Logic Programming 1992: Volume 14 , Issue Index. Digitized from IA1652909-07 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1992-08_13_4 . Next issue: sim_journal-of-logic-and-algebraic-programming_1992_14_contents .

The Journal of Logic and Algebraic Programming 1996: Volume 29 , Issue CONTENTS. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1996_29_index . Next issue: sim_journal-of-logic-and-algebraic-programming_october-december-1996_29_1-3 .

The Journal of Logic and Algebraic Programming 1998: Volume 34 , Issue Index. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1997-12_33_3 . Next issue: sim_journal-of-logic-and-algebraic-programming_1998_34_contents . Note: This issue has no cover

The Journal of Logic and Algebraic Programming 1999: Volume 38 , Issue CONTENTS. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1999_38_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1999-01_38_1 . Note: This issue has no cover

The Journal of Logic and Algebraic Programming 1999: Volume 38 , Issue CONTENTS. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1999_38_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1999-01_38_1 . Note: This issue has no cover

The Journal of Logic and Algebraic Programming 1999: Volume 38 , Issue CONTENTS. Digitized from IA1652909-05 . Previous issue: sim_journal-of-logic-and-algebraic-programming_1999_38_index . Next issue: sim_journal-of-logic-and-algebraic-programming_1999-01_38_1 . Note: This issue has no cover