Browsing by Author "Claybrook, Billy G."

Now showing 1 - 7 of 7
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    An Artificial Intelligence Approach to the Symbolic Factorization of Multivariable Polynomials
    Claybrook, Billy G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1974)
    A new heuristic factorization scheme that uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with integer coefficients and an arbitrary number of variables and terms is described. The factorization scheme makes extensive use of Artificial Intelligence techniques, e.g. model-building, learning, and automatic classification in an attempt to reduce the amount of searching for the irreducible factors of a polynomial. The approach taken to polynomial factorization is quite different from previous attempts because: (1) it is distinct from numerial techniques, (2) possibilities for terms in a factor are generated from the terms in the polynomial, and (3) a reclassification technique is used to allow the application of different sets of heuristics to a polynomial during factorization attempts on it. Tables are presented that demonstrate the importance of learning to the efficiency of operation of the scheme. Factorizat5.on times of polynomials factored by both the scheme described in this paper and Wang's implementation of Berlekamp's algorithm are given and compared and an analysis of variance experiment provides an indication of the significant sources of variation influencing the factorization time.
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    The Dynamic Creation And Modification of Heuristics in a Learning Program
    Claybrook, Billy G.; Nance, Richard E. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1973)
    POLY FACT is a learning program that attempts to factor multivariable polynomials. The program has been successful in factoring polynomials (in simplified form) with a maximum of 84 terms, each term consisting of as many as five variables and a maximum degree of 67. The complexity of this learning task placed unusual requirements on the representation of heuristics. By using the first-order predicate calculus notation, we enable the creation and modification of heuristics dynamically during program execution. Constraints on the creation process are implemented in a series of tables by which one can alter the flexibility given to the program. Execution of heuristics begins with a translation of the predicate calculus representation to a reverse Polish string, followed by the interpretive evaluation of the Polish string. A general procedure for developing and implementing the predicate calculus representation is suggested.
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    A File Definition Facility for File Structures
    Claybrook, Billy G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1974)
    This paper describes a file definition facility (FDF) for defining files as graph structures. The structure of the file is explicitly declared in the file definition. Primitive functions(from graph theory), operators, and the format of the definition statements are given. The combination of functions and operators appear as directives to the programming system for structuring files. Several simple examples are given to illustrate the use of the FDF. The data organization for the implementation of this facility is described in detail. Problems of considerable importance that are treated are. (1) garbage collection, (2) template construction, and (3) runtime address calculation. The external definitions are represented internally by descriptors. The format of the descriptors is given and a discussion of the items in the descriptors is presented.
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    Fol: A Language for Implementing File Organizations for Information Storage And Retrieval Systems
    Claybrook, Billy G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1973)
    The language FOL is described. FOL facilitates the implementation of file organizations for IS & R systems. FOL is implemented in a list processing language LPL. Files in FOL are interepreted as a list of records, where each record is equivalent to a node structure. A description of LPL is also included.
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    Language Extensions for Specifying Access Control Policies in Programming Languages
    Claybrook, Billy G.; Hartson, H. Rex (Department of Computer Science, Virginia Polytechnic Institute & State University, 1980)
    The scope rules in programming languages control the sharing of data among program units-e.g., blocks and procedures. Typically, scope rules provide an all-or-nothing kind of access control. A wide range of programming problems exist which require finer access control as well as considerable sophistication for the implementation of access control policies on high-level data objects such as files. This paper presents a number of language extensions that permit the programmer to specify the degree of access control for each abstract object that a program unit can manipulate. An attempt has been made to keep the number of extensions as small as possible and yet allow the user conveniently to specify the access control policies that he desires. Some of the extensions permit access policies to be specified such that access correctness can be completely determined at compile time; other extensions permit policies to be specified that require some access checking to be done at runtime in order to ensure access correctness. The extensions have been developed such that subsets can be selected and implemented in programming languages to provide various access control policies.
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    Learning as a Problem Solving Tool
    Claybrook, Billy G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1974)
    This paper explores the use of learning as a practical tool in problem solving. The idea that learning should and eventually will be a vital component of most Artificial Intelligence programs is pursued. Current techniques in learning systems are compared. A detailed discussion of the problems of representing, modifying, and creating heuristics is given. Some of the questions asked (and answered) in the paper are: (1) how does the choice of representation affect the potential for learning?, (2) what techniques have been used to date and how do they compare?, i.e. first-order predicate calculus vs. production rules vs. Winston's representation, and (3) exactly how are heuristics modified in the existing systems and what do these techniques have in common? A discussion of the credit assignment problem as it relates to learning under the various schemes of representation is also presented.
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    Lpl: A Generalized List Processing Language
    Claybrook, Billy G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1973)
    The paper describes LFL, a generalized list processing language. LFL allows the user to define multiple cell structures and cell sizes at runtime, thereby allowing nonhomogeneous list structures. The paper examines the problems associated with list tracing in systems allowing multiple cell-types. Complex list tracing during garbage collection in LFL is avoided: (1) by creating a doubly-linked super list of all allocated cells and (2) by using a reference count scheme. No marking phase is required for garbage collection. The problem of developing insertion and deletion procedures for lists with cells having multiple types of pointer structures is discussed and LFL solutions are given. LPL statements can handle singly-linked, doubly-linked, left-right-linked, and some multi-linked pointer structures automatically. The design philosophy and the data organization for LPL are discussed in detail. Examples of the definition of cell structures are given, and all of the LPL list manipulation and creation statements arc examined and discussed.