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12
Experiments with Proof Plans for Induction
 Journal of Automated Reasoning
, 1992
"... The technique of proof plans, is explained. This technique is used to guide automatic inference in order to avoid a combinatorial explosion. Empirical research is described to test this technique in the domain of theorem proving by mathematical induction. Heuristics, adapted from the work of Boye ..."
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Cited by 94 (32 self)
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The technique of proof plans, is explained. This technique is used to guide automatic inference in order to avoid a combinatorial explosion. Empirical research is described to test this technique in the domain of theorem proving by mathematical induction. Heuristics, adapted from the work of Boyer and Moore, have been implemented as Prolog programs, called tactics, and used to guide an inductive proof checker, Oyster. These tactics have been partially specified in a metalogic, and the plan formation program, clam, has been used to reason with these specifications and form plans. These plans are then executed by running their associated tactics and, hence, performing an Oyster proof. Results are presented of the use of this technique on a number of standard theorems from the literature. Searching in the planning space is shown to be considerably cheaper than searching directly in Oyster's search space. The success rate on the standard theorems is high. Keywords Theorem prov...
Information Filtering: Selection Mechanisms In Learning Systems
, 1989
"... interpreter for logic programs (Sterling & Shapiro, 1986)...................138 1 1. INTRODUCTION The most important outcome of AI research during the 70s was the general acceptance of the major role of knowledge in intelligent systems (Buchanan & Feigenbaum, 1982). Lenat and Feigenbaum (1989) call ..."
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Cited by 37 (8 self)
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interpreter for logic programs (Sterling & Shapiro, 1986)...................138 1 1. INTRODUCTION The most important outcome of AI research during the 70s was the general acceptance of the major role of knowledge in intelligent systems (Buchanan & Feigenbaum, 1982). Lenat and Feigenbaum (1989) call this belief the knowledge as power hypothesis and assert it as: "The knowledge principle (KP) A system exhibits intelligent understanding and action at a high level of competence primarily because of the specific knowledge that it can bring to bear: the concepts, facts, representations, methods, models, metaphors, and heuristics about its domain of endeavor." Or as Buchanan and Feigenbaum (Buchanan & Feigenbaum, 1982) put it, "the power of an intelligent program to perform its task well depends primarily on the quantity and quality of knowledge it has about that task." Thus, it is not surprising that the general attitude toward knowledge was a greedy one  grab as much knowledge as you ca...
Metaprogramming in Logic
 Encyclopedia of Computer Science and Technology
, 1994
"... In this review of metaprogramming in logic we pay equal attention to theoretical and practical issues: the contents range from mathematical and logical preliminaries to implementation and applications in, e.g., software engineering and knowledge representation. The area is one in rapid development b ..."
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Cited by 17 (0 self)
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In this review of metaprogramming in logic we pay equal attention to theoretical and practical issues: the contents range from mathematical and logical preliminaries to implementation and applications in, e.g., software engineering and knowledge representation. The area is one in rapid development but we have emphasized such issues that are likely to be important for future metaprogramming languages and methodologies. 1 Introduction The term `metaprogramming' relates to `programming' as `metalanguage' relates to `language' and `metalogic' to `logic': programming where the data represent programs. It should be no surprise that metaprogramming with logic programming languages takes advantage of many results from metalogic. In the most general interpretation we would say that `metaprogramming ' refers to any kind of computer programming where the input or output represents programs. We will refer to a program of this kind as a metaprogram and to its data as object programs. Analogousl...
Implementing Prolog Extensions : A Parallel Inference Machine
 Machine, Proceedings of the 1992 International Conference on Fifth Generation Computer Systems, ICOT
, 1992
"... We present in this paper a general inference machine for building a large class of metainterpreters. In particular, this machine is suitable for implementing extensions of Prolog with nonclassical logics. We give the description of the abstract machine model and an implementation of this machine in ..."
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Cited by 8 (1 self)
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We present in this paper a general inference machine for building a large class of metainterpreters. In particular, this machine is suitable for implementing extensions of Prolog with nonclassical logics. We give the description of the abstract machine model and an implementation of this machine in a fast language (ADA), along with a discussion on why and how parallelism can easily increase speed, with numerical results of sequential and parallel implementation. 1 Introduction In order to get closer to human reasoning, computer systems, and especially logic programming systems, have to deal with various concepts such as time, belief, knowledge, contexts, etc: : : Prolog is just what is needed to handle the Horn clause fragment of first order logic, but what about nonclassical logics? Just suppose we want to represent in Prolog time, knowledge, hypotheses, or two of them at the same time; or to organize our program in modules, to have equational theories, to treat fuzzy predicates or...
MetaProgramming for Generalized Horn Clause Logic
, 1996
"... . In conventional logic programming systems, control information is expressed by clause and goal order and by purely procedural constructs, e.g., the Prolog cut. This approach destroys the equivalence of declarative and procedural semantics in logic programs. In this paper, we argue that in order to ..."
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Cited by 8 (6 self)
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. In conventional logic programming systems, control information is expressed by clause and goal order and by purely procedural constructs, e.g., the Prolog cut. This approach destroys the equivalence of declarative and procedural semantics in logic programs. In this paper, we argue that in order to comply with the logic programming paradigm, control information should also be expressed declaratively. A program should be divided into a logical theory that specifies the problem to be solved and control information that specifies the strategy of the deduction process. Control information is expressed through meta level control clauses. These control clauses are evaluated dynamically in order to select the subgoal that will be resolved next and to select the resolving clause. Program clauses have guards that allow clause determinism to be expressed. A major design goal for the presented work is to keep the declarative and the procedural semantics of logic programs equivalent. The emphasis...
A Customized Logic Paradigm for Reasoning about Models
 In QR96
, 1996
"... Modeling is the process of constructing a suitable model of a target system for a given task. The work described in this proposal uses ordinary differential equations as models of physical systems. Ordinary differential equations are one common form of dynamic system model. Other classes of models r ..."
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Cited by 5 (4 self)
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Modeling is the process of constructing a suitable model of a target system for a given task. The work described in this proposal uses ordinary differential equations as models of physical systems. Ordinary differential equations are one common form of dynamic system model. Other classes of models range from partial differential equations to abstract models that only capture the highlevel qualitative structure of the target system. The task of finding a model that matches the observed behavior of a target system is often called system identification. Typically, in the hierarchy from more abstract to less abstract models, the model of choice is the one that is just detailed enough to account for the properties and perspectives of interest for the task at hand. The main goal of the proposed work is to design and implement a knowledge representation framework that allows a computer program to reason about physical systems and candidate models in such a way as to find the right model at ...
Multimodal Reasoning for Automatic Model Construction
 In Proceedings of AAAI98
, 1998
"... This paper describes a program called Pret that automates system identication, the process of nding a dynamical model of a blackbox system. Pret performs both structural identication and parameter estimation by integrating several reasoning modes: qualitative reasoning, qualitative simulation, ..."
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Cited by 4 (2 self)
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This paper describes a program called Pret that automates system identication, the process of nding a dynamical model of a blackbox system. Pret performs both structural identication and parameter estimation by integrating several reasoning modes: qualitative reasoning, qualitative simulation, numerical simulation, geometric reasoning, constraint reasoning, resolution, reasoning with abstraction levels, declarative metalevel control, and a simple form of truth maintenance. Unlike other modeling programs that map structural or functional descriptions to model fragments, Pret combines hypotheses about the mathematics involved into candidate models that are intelligently tested against observations about the target system. We give two examples of system identication tasks that this automated modeling tool has successfully performed. The rst, a simple linear system, was chosen because it facilitates a brief and clear presentation of Pret's features and reasoning t...
Opportunistic Modeling
 In IJCAI97 Workshop on Engineering Problems for Qualitative Reasoning
, 1997
"... System identification  the process of inferring an internal model from external observations of a system  is a routine and difficult problem faced by engineers in a variety of domains. Typically, in the hierarchy from moreabstract to lessabstract models, the model of choice is the one that i ..."
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Cited by 4 (3 self)
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System identification  the process of inferring an internal model from external observations of a system  is a routine and difficult problem faced by engineers in a variety of domains. Typically, in the hierarchy from moreabstract to lessabstract models, the model of choice is the one that is just detailed enough to account for the properties and perspectives that are of interest for the task at hand. The main goal of the work described here was to design and implement a knowledge representation framework that allows a computer program to reason about physical systems and candidate models  ordinary differential equations (ODEs), specifically  in such a way as to find the right model at the right abstraction level as quickly as possible. A key observation about the modeling process is the following. Not only is the resulting model the least complex of all possible ones, but also the reasoning during model construction takes place at the highest possible level at any time. ...
Declarative Meta Level Control for Logic Programs
 In Proceedings des Ersten RussischDeutschen Symposiums zu Intelligenten Informationstechnologien und Expertensystemen (anläßlich des Internationalen Forums für Informatisierung, IFI95), Moskau
, 1995
"... . In conventional logic programming systems, control information is expressed by clause and goal order and by purely procedural constructs, e.g., the Prolog cut. This approach destroys the equivalence of declarative and procedural semantics in logic programs. In this paper, we argue that in order to ..."
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Cited by 3 (2 self)
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. In conventional logic programming systems, control information is expressed by clause and goal order and by purely procedural constructs, e.g., the Prolog cut. This approach destroys the equivalence of declarative and procedural semantics in logic programs. In this paper, we argue that in order to comply with the logic programming paradigm, control information should also be expressed declaratively. A program should be divided into a logical theory that specifies the problem to be solved and control information that specifies the strategy of the deduction process. Control information is expressed through meta level control clauses. These control clauses are evaluated dynamically in order to select the subgoal that will be resolved next and to select the resolving clause. Program clauses have guards that allow clause determinism to be expressed. A major design goal for the presented work is to keep the declarative and the procedural semantics of logic programs equivalent. The emphasis...
ACTP: A Configurable TheoremProver
 Data & Knowledge Engineering
, 1994
"... There has been a considerable amount of research into the provision of explicit representation of control regimes for resolutionbased theorem provers. ..."
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Cited by 2 (2 self)
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There has been a considerable amount of research into the provision of explicit representation of control regimes for resolutionbased theorem provers.