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Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

Tabling has been used for some time to improve efficiency of Prolog programs by memorizing answered queries. The same idea can be naturally used to memorize visited states during search for planning. In this paper we present a planner developed in the Picat language to solve the Petrobras planning problem. Picat is a novel Prolog-like language that provides pattern matching, deterministic and non-deterministic rules, and tabling as its core modelling and solving features. We demonstrate these capabilities using the Petrobras problem, where the goal is to plan transport of cargo items from ports to platforms using vessels with limited capacity. Monte Carlo Tree Search has been so far the best technique to tackle this problem and we will show that by using tabling we can achieve much better runtime efficiency and better plan quality.

The work conducted this year followed the projections set forth in the grant proposal rather closely. On the theoretical side, the investigators have continued to explore questions of the logical status of some of the standard data structures involved in various artificial intelligence applications involving knowledge bases. The greatest attention has been focused on frames. Exploration of the axiomatization and representation of semantic nets by similar methods has been carried out. The nodes of the net are treated by methods similar to frames. Most of the attention here has focused on the work of Woods and Brachman and the KLONE formalism. The investigators have conducted a number of explorations with their existing experimental metaProlog simulator. This simulation was coded in Edinburgh Prolog and run on Syracuse University's DEC-10 computer. Progress in these areas is discussed in greater detail in this interim report. (Author)

The digital logic simulator, LOGSIM248, a re-engineered version of LOGSIM, version 5.5, has been implemented as a component of the digital design environment, IDIET (Integrated Digital Engineering Tool). This new design expands the capabilities of the older version by improving run time performance, maintainability, and compatability. Written in the C programming language, LOGSIM248 boasts looser coupling between functional modules while exhibiting greater functional cohesion within these modules. As an integral part of IDIET, the simulator overcomes difficulties created by the complicated user interface of earlier versions. With greater run time performance as a goal, this new simulator was studied and adapted to produce a concurrent implementation. Here, several roadblocks were encountered which essentially showed this algorithm and data structure implementation to be difficult to parallelize at best.

Two programming paradigms, logic programming and functional programming, are discussed in detail with emphasis on the particular advantages and disadvantages of each paradigm. The integration of these two programming paradigms is explored based on the notion that declarative sorts of knowledge (facts and logical relationships) should be expressed in a declarative way, and that procedural sorts of knowledge (manipulation, control, and utilization of knowledge) should be expressed in a procedural way. Toward this end, the conceptual framework for an integrated language is established, and the basic features of the language are outlined. (Author)

Two programming paradigms, logic programming and functional programming, are discussed in detail with emphasis on the particular advantages and disadvantages of each paradigm. The integration of these two programming paradigms is explored based on the notion that declarative sorts of knowledge (facts and logical relationships) should be expressed in a declarative way, and that procedural sorts of knowledge (manipulation, control, and utilization of knowledge) should be expressed in a procedural way. Toward this end, the conceptual framework for an integrated language is established, and the basic features of the language are outlined. (Author)

Two programming paradigms, logic programming and functional programming, are discussed in detail with emphasis on the particular advantages and disadvantages of each paradigm. The integration of these two programming paradigms is explored based on the notion that declarative sorts of knowledge (facts and logical relationships) should be expressed in a declarative way, and that procedural sorts of knowledge (manipulation, control, and utilization of knowledge) should be expressed in a procedural way. Toward this end, the conceptual framework for an integrated language is established, and the basic features of the language are outlined. (Author)

Two programming paradigms, logic programming and functional programming, are discussed in detail with emphasis on the particular advantages and disadvantages of each paradigm. The integration of these two programming paradigms is explored based on the notion that declarative sorts of knowledge (facts and logical relationships) should be expressed in a declarative way, and that procedural sorts of knowledge (manipulation, control, and utilization of knowledge) should be expressed in a procedural way. Toward this end, the conceptual framework for an integrated language is established, and the basic features of the language are outlined. (Author)

This volume contains the papers presented at Arg-LPNMR 2016: First International Workshop on Argumentation in Logic Programming and Nonmonotonic Reasoning held on July 8-10, 2016 in New York City, NY.

This volume contains the papers presented at Arg-LPNMR 2016: First International Workshop on Argumentation in Logic Programming and Nonmonotonic Reasoning held on July 8-10, 2016 in New York City, NY.

Disjunctive Logic Programming (\DLP) is an advanced formalism for Knowledge Representation and Reasoning (KRR). \DLP is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class $\SigmaP{2}$ ($\NP^{\NP}$). Importantly, the \DLP encodings are often simple and natural. In this paper, we single out some limitations of \DLP for KRR, which cannot naturally express problems where the size of the disjunction is not known ``a priori'' (like N-Coloring), but it is part of the input. To overcome these limitations, we further enhance the knowledge modelling abilities of \DLP, by extending this language by {\em Parametric Connectives (OR and AND)}. These connectives allow us to represent compactly the disjunction/conjunction of a set of atoms having a given property. We formally define the semantics of the new language, named $DLP^{\bigvee,\bigwedge}$ and we show the usefulness of the new constructs on relevant knowledge-based problems. We address implementation issues and discuss related works.

Disjunctive Logic Programming (\DLP) is an advanced formalism for Knowledge Representation and Reasoning (KRR). \DLP is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class $\SigmaP{2}$ ($\NP^{\NP}$). Importantly, the \DLP encodings are often simple and natural. In this paper, we single out some limitations of \DLP for KRR, which cannot naturally express problems where the size of the disjunction is not known ``a priori'' (like N-Coloring), but it is part of the input. To overcome these limitations, we further enhance the knowledge modelling abilities of \DLP, by extending this language by {\em Parametric Connectives (OR and AND)}. These connectives allow us to represent compactly the disjunction/conjunction of a set of atoms having a given property. We formally define the semantics of the new language, named $DLP^{\bigvee,\bigwedge}$ and we show the usefulness of the new constructs on relevant knowledge-based problems. We address implementation issues and discuss related works.

Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems such as $\mathcal{AL}$-log that integrates the description logic $\mathcal{ALC}$ and the function-free Horn clausal language \textsc{Datalog}. In this paper we consider the problem of automating the acquisition of these rules for the Semantic Web. We propose a general framework for rule induction that adopts the methodological apparatus of Inductive Logic Programming and relies on the expressive and deductive power of $\mathcal{AL}$-log. The framework is valid whatever the scope of induction (description vs. prediction) is. Yet, for illustrative purposes, we also discuss an instantiation of the framework which aims at description and turns out to be useful in Ontology Refinement. Keywords: Inductive Logic Programming, Hybrid Knowledge Representation and Reasoning Systems, Ontologies, Semantic Web. Note: To appear in Theory and Practice of Logic Programming (TPLP)

We provide a denotational semantics for first-order logic that captures the two-level view of the computation process typical for constraint programming. At one level we have the usual program execution. At the other level an automatic maintenance of the constraint store takes place. We prove that the resulting semantics is sound with respect to the truth definition. By instantiating it by specific forms of constraint management policies we obtain several sound evaluation policies of first-order formulas. This semantics can also be used a basis for sound implementation of constraint maintenance in presence of block declarations and conditionals.

This paper treats logic programming with three kinds of negation: default, weak and strict negations. A 3-valued logic model theory is discussed for logic programs with three kinds of negation. The procedure is constructed for negations so that a soundness of the procedure is guaranteed in terms of 3-valued logic model theory.

45 p. 28 cm

Book Source: Digital Library of India Item 2015.193856 dc.contributor.author: Vinod Kumar Dashora dc.date.accessioned: 2015-07-08T03:29:09Z dc.date.available: 2015-07-08T03:29:09Z dc.date.digitalpublicationdate: 2005-09-27 dc.identifier.barcode: 1990010092145 dc.identifier.origpath: /rawdataupload/upload/0092/145 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/193856 dc.description.scannerno: 14 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 74 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Indian Institute Of Technology Kanpur dc.rights: Out_of_copyright dc.source.library: Indian Institute Of Technology Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Computer Science & Engineering dc.title: Meta-control Amp Functional Relations In Logic Programming

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Includes bibliographies

Inductions and game semantics are two useful extensions to traditional logic programming. To be specific, inductions can capture a wider class of provable formulas in logic programming. Adopting game semantics can make logic programming more interactive. In this paper, we propose an execution model for a logic language with these features. This execution model follows closely the reasoning process in real life.

We present a CLP(FD)-based constraint solver able to deal with unbounded domains. It is based on constraint propagation, resorting to enumeration if all other methods fail. An important aspect is detecting when enumeration was complete and if this has an impact on the soundness of the result. We present a technique which guarantees soundness in the following way: if the constraint solver finds a solution it is guaranteed to be correct; if the constraint solver fails to find a solution it can either return the result "definitely false" in case it knows enumeration was exhaustive, or "unknown" in case it was aborted. The technique can deal with nested universal and existential quantifiers. It can easily be extended to set comprehensions and other operators introducing new quantified variables. We show applications in data validation and proof.

This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for principled reasons not addressable with probabilistic means); and to provide evidence that logic-based methods can well support reasoning with uncertainty. For the latter claim, two paradigmatic examples are presented: Logic Programming with Kleene semantics for modelling reasoning from information in a discourse, to an interpretation of the state of affairs of the intended model, and a neural-symbolic implementation of Input/Output logic for dealing with uncertainty in dynamic normative contexts.

We propose a purely extensional semantics for higher-order logic programming. In this semantics program predicates denote sets of ordered tuples, and two predicates are equal iff they are equal as sets. Moreover, every program has a unique minimum Herbrand model which is the greatest lower bound of all Herbrand models of the program and the least fixed-point of an immediate consequence operator. We also propose an SLD-resolution proof procedure which is proven sound and complete with respect to the minimum model semantics. In other words, we provide a purely extensional theoretical framework for higher-order logic programming which generalizes the familiar theory of classical (first-order) logic programming.

We propose a purely extensional semantics for higher-order logic programming. In this semantics program predicates denote sets of ordered tuples, and two predicates are equal iff they are equal as sets. Moreover, every program has a unique minimum Herbrand model which is the greatest lower bound of all Herbrand models of the program and the least fixed-point of an immediate consequence operator. We also propose an SLD-resolution proof procedure which is proven sound and complete with respect to the minimum model semantics. In other words, we provide a purely extensional theoretical framework for higher-order logic programming which generalizes the familiar theory of classical (first-order) logic programming.

We begin with a review of intuitionistic non-commutative linear logic (INCLL), a refinement of linear logic with an inherent notion of order proposed by the authors in prior work. We then develop a logic programming interpretation for INCLL in two steps: (1) we give a system of ordered uniform derivations which is sound and complete with respect to INCLL, and (2) we present a model of resource consumption which removes non-determinism from ordered resource allocation during search for uniform derivations. We also illustrate the expressive power of the resulting ordered linear logic programming language through some examples, including programs for merge sort, insertion sort, and natural language parsing.

This paper describes applications of logic programming technology to the teaching of the inductive method in computer science and mathematics. It discusses the nature of inductive thought and its place in those fields of inquiry, arguing that a complete logic programming system for supporting inductive inference is not only feasible but necessary. A sample dialog from the Prologb system is included, along with an overview of the Prologb language and some details about classroom experiences using the system. (Author/BEW)

This paper describes applications of logic programming technology to the teaching of the inductive method in computer science and mathematics. It discusses the nature of inductive thought and its place in those fields of inquiry, arguing that a complete logic programming system for supporting inductive inference is not only feasible but necessary. A sample dialog from the Prologb system is included, along with an overview of the Prologb language and some details about classroom experiences using the system. (Author/BEW)

This paper describes applications of logic programming technology to the teaching of the inductive method in computer science and mathematics. It discusses the nature of inductive thought and its place in those fields of inquiry, arguing that a complete logic programming system for supporting inductive inference is not only feasible but necessary. A sample dialog from the Prologb system is included, along with an overview of the Prologb language and some details about classroom experiences using the system. (Author/BEW)

This paper describes applications of logic programming technology to the teaching of the inductive method in computer science and mathematics. It discusses the nature of inductive thought and its place in those fields of inquiry, arguing that a complete logic programming system for supporting inductive inference is not only feasible but necessary. A sample dialog from the Prologb system is included, along with an overview of the Prologb language and some details about classroom experiences using the system. (Author/BEW)

The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.

The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.

"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.

The initial version of PRISM uses a simulation of the ZMOB hardware, and has been fully tested and debugged. In addition, several enhancements were made to PRISM to permit experimental analyses to be made, and to incorporate additional features to take full advantage of parallelism in a problem solving environment. Tracing and a statistical gathering package were added to permit experimental analysis. An AND-parallelism capability was added to achieve a second version of the PRISM system, and other features were added to the system to more fully exploit parallelism. Preliminary application and evaluation studies were performed.

This paper addresses semantic and expressiveness issues for temporal logic programming and in particular for the TEMPLOG language proposed by Abadi and Manna. Two equivalent formulations of TEMPLOG's declarative semantics are given: in terms of a minimal Herbrand model and in terms of a least fixpoint. By relating these semantics to TEMPLOG's operational semantics, we prove the completeness of the resolution proof system underlying TEMPLOG's execution mechanism. To study TEMPLOG's expressiveness, we consider its propositional version. We show how propositional TEMPLOG programs can be translated into a temporal fixpoint calculus and prove that they can express essentially all regular properties of sequences.

This paper addresses semantic and expressiveness issues for temporal logic programming and in particular for the TEMPLOG language proposed by Abadi and Manna. Two equivalent formulations of TEMPLOG's declarative semantics are given: in terms of a minimal Herbrand model and in terms of a least fixpoint. By relating these semantics to TEMPLOG's operational semantics, we prove the completeness of the resolution proof system underlying TEMPLOG's execution mechanism. To study TEMPLOG's expressiveness, we consider its propositional version. We show how propositional TEMPLOG programs can be translated into a temporal fixpoint calculus and prove that they can express essentially all regular properties of sequences.

Book by V.E. Wolfengagen "Combinatory Logic in Programming. Computations with Objects Through Examples and Exercises". 2-nd ed. -- Moscow, Center JurInfoR, 2003. X+336 p. The book is intended for computer science students, programmers and professionals who have already got acquainted with the basic courses and background on discrete mathematics. It may be used as a textbook for graduate course on theoretical computer science. The book introduces a reader to the conceptual framework for thinking about computations with the objects. The several areas of theoretical computer science are covered, including the following: type free and typed lambda-calculus and combinatory logic with applications, evaluation of expressions, computations in a category. The topics, covered in the book accumulated much experience in teaching these subjects in graduate computer science courses. A rich set of examples and exercises, including solutions, has been prepared to stimulate the self studying and to make easier the job of instructor.

Book by V.E. Wolfengagen "Combinatory Logic in Programming. Computations with Objects Through Examples and Exercises". 2-nd ed. -- Moscow, Center JurInfoR, 2003. X+336 p. The book is intended for computer science students, programmers and professionals who have already got acquainted with the basic courses and background on discrete mathematics. It may be used as a textbook for graduate course on theoretical computer science. The book introduces a reader to the conceptual framework for thinking about computations with the objects. The several areas of theoretical computer science are covered, including the following: type free and typed lambda-calculus and combinatory logic with applications, evaluation of expressions, computations in a category. The topics, covered in the book accumulated much experience in teaching these subjects in graduate computer science courses. A rich set of examples and exercises, including solutions, has been prepared to stimulate the self studying and to make easier the job of instructor.

Book by V.E. Wolfengagen "Combinatory Logic in Programming. Computations with Objects Through Examples and Exercises". 2-nd ed. -- Moscow, Center JurInfoR, 2003. X+336 p. The book is intended for computer science students, programmers and professionals who have already got acquainted with the basic courses and background on discrete mathematics. It may be used as a textbook for graduate course on theoretical computer science. The book introduces a reader to the conceptual framework for thinking about computations with the objects. The several areas of theoretical computer science are covered, including the following: type free and typed lambda-calculus and combinatory logic with applications, evaluation of expressions, computations in a category. The topics, covered in the book accumulated much experience in teaching these subjects in graduate computer science courses. A rich set of examples and exercises, including solutions, has been prepared to stimulate the self studying and to make easier the job of instructor.

This paper shows how to apply memoization (caching of subgoals and associated answer substitutions) in a constraint logic programming setting. The research is is motivated by the desire to apply constraint logic programming (CLP) to problems in natural language processing that involve (constraint) interleaving or coroutining, such as GB and HPSG parsing.

Prioritized default reasoning has illustrated its rich expressiveness and flexibility in knowledge representation and reasoning. However, many important aspects of prioritized default reasoning have yet to be thoroughly explored. In this paper, we investigate two properties of prioritized logic programs in the context of answer set semantics. Specifically, we reveal a close relationship between mutual defeasibility and uniqueness of the answer set for a prioritized logic program. We then explore how the splitting technique for extended logic programs can be extended to prioritized logic programs. We prove splitting theorems that can be used to simplify the evaluation of a prioritized logic program under certain conditions.

Approved F.elease 20055 $S RDP78B0lPA000100110011-8 hd' I C/PLDS/D/6-7 1 6 11 January 1966 S ? MEMQRN ( Chief, Technical Intel I ige Division ATTENTION: Chief, TAB/Tit) SUBJECTS Additional Pre"wainq and Logic Circuitry for the AP-3 Analytical Plotting System REFERS : I - Contract 1. In accordance with your request, IIpersonnel have been Invited to NPIC on January 25, 1966 to obta n he unclassified information required to enable them to submit a proposal to incorporate a strip photography capability in the AP-3 system. 2. 0 tentatively plans to send three people; one engineer and two programmers. The two programs srs do not hold Agency clearance but since the mathematical model Is unclassified this should not pose it problem. The project eng l neer, holds an Agency Secret clearance. 3. I f appropriate arrangements can be made, It appears that it would be eat, advantageous to set up this meting In the T I D con f erence r o o m . I f at all possible, the consultants that prepared the mathemat i ca l model should be present, as well TiD and IPD personnel as the situation requires. 4. Due to the urgent nature of th i s otter, an early r^ep l y I s requested. Declass Review by NGA. Colonel, USAF Assistant for Plans and Development Distribution: Original and I - Addresses I - Ch/TAB/TID I - Ch/IPD I - Ch/PB/IPD I - Project File/DB (#998125) 1 - Chrono/DB NPIC/P&DS/DB: Approved For Release 2 ~L IfIA-RDP78B04770A000100110011- 25 25X 25X