The aim of this study is threefold. First, a qualitative information security risk survey is implemented in human resources department of a logistics company. Second, a machine learning risk classification and predict...
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A lack of adequate and flexible topology support in the popular message passing systems such as Parallel Virtual Machine was a major factor in the development of our Virtual Process Topology Environment. This parallel...
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We analyze the search space of two clause-based proof procedures, the Model Elimination procedure and Near-Horn Prolog, both of Loveland. We study how the search space changes with respect to the degree of how “non-H...
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Genetic programming is known to be capable of creating designs that satisfy prespecified high-level design requirements for analog electrical circuits and other complex structures. However, in the real world, it is of...
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作者：
LENAT, DBComputer Science Department
Stanford University Stanford CA 94305 U.S.A.[∗]The author is an assistant professor of Computer Science at Stanford University a member of that university"s Heuristic Programming Project and a consultant for CIS at XEROX PARC.
Builders of expert rule-based systems attribute the impressive performance of their programs to the corpus of knowledge they embody: a large network of facts to provide breadth of scope, and a large array of informal ...
Builders of expert rule-based systems attribute the impressive performance of their programs to the corpus of knowledge they embody: a large network of facts to provide breadth of scope, and a large array of informal judgmental rules (heuristics) which guide the system toward plausible paths to follow and away from implausible ones. Yet what is the nature of heuristics? What is the source of their power? How do they originate and evolve? By examining two case studies, the am and eurisko programs, we are led to some tentative hypotheses: Heuristics are compiled hindsight, and draw their power from the various kinds of regularity and continuity in the world; they arise through specialization, generalization, and—surprisingly often—analogy. Forty years ago, Polya introduced Heuretics as a separable field worthy of study. Today, we are finally able to carry out the kind of computation-intensive experiments which make such study possible.
The unification problem for terms containing associative and commutative functions is of importance in theorem provers based on term rewriting and resolution methods as well as in logic programming. The complexity of ...
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This paper sets some context, raises issues, and provides our initial thinking on the characteristics of effective rapid prototyping techniques. After discussing the role rapid prototyping techniques can play in the s...
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ISBN:
(纸本)089791094X
This paper sets some context, raises issues, and provides our initial thinking on the characteristics of effective rapid prototyping techniques. After discussing the role rapid prototyping techniques can play in the software lifecycle, the paper looks at possible technical approaches including: heavily parameterized models, reusable software, rapid prototyping languages, prefabrication techniques for system generation, and reconfigurable test harnesses. The paper concludes that a multi-faceted approach to rapid prototyping techniques is needed if we are to address a broad range of applications successfully - no single technical approach suffices for all potentially desirable applications.
This paper develops a formal string diagram language for monoidal closed categories. Previous work has shown that string diagrams for freely generated symmetric monoidal categories can be viewed as hypergraphs with in...
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Boolean Differential Calculus (BDC) extends Boolean *** Boolean algebra is focused on values of logic functions,BDC allows the evaluation of changes of the function values. Such changes can be investigated between cer...
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ISBN:
(纸本)9781608451821
Boolean Differential Calculus (BDC) extends Boolean *** Boolean algebra is focused on values of logic functions,BDC allows the evaluation of changes of the function values. Such changes can be investigated between certain pairs of function values as well as regarding whole subspaces. Due to the same basic data structures, BDC can be applied to any task described by logic functions and equations together with the Boolean *** used is BDC in analysis, synthesis, and testing of digital circuits. In this chapter, we introduce basic definitions of BDC together with some typical applications.
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