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The empirical case for two systems of reasoning

by Steven A. Sloman , 1996
"... Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations ref ..."
Abstract - Cited by 669 (4 self) - Add to MetaCart
and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization.

Modeling and simulation of genetic regulatory systems: A literature review

by Hidde De Jong - JOURNAL OF COMPUTATIONAL BIOLOGY , 2002
"... In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between ..."
Abstract - Cited by 738 (14 self) - Add to MetaCart
, ordinary and partial differential equations, qualitative differential equations, stochastic equations, and rule-based formalisms. In addition, the paper discusses how these formalisms have been used in the simulation of the behavior of actual regulatory systems.

An Analysis of First-Order Logics of Probability

by Joseph Y. Halpern - Artificial Intelligence , 1990
"... : We consider two approaches to giving semantics to first-order logics of probability. The first approach puts a probability on the domain, and is appropriate for giving semantics to formulas involving statistical information such as "The probability that a randomly chosen bird flies is greater ..."
Abstract - Cited by 314 (17 self) - Add to MetaCart
: We consider two approaches to giving semantics to first-order logics of probability. The first approach puts a probability on the domain, and is appropriate for giving semantics to formulas involving statistical information such as "The probability that a randomly chosen bird flies

Learning logical definitions from relations

by J. R. Quinlan - MACHINE LEARNING , 1990
"... This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism. This new system has been applied successfully to several tasks taken fro ..."
Abstract - Cited by 935 (8 self) - Add to MetaCart
This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism. This new system has been applied successfully to several tasks taken

An almost ideal demand system.

by Angus Deaton , John Muellbauer - American Economic Review, , 1980
"... Ever since Richard Stone (1954) first estimated a system of demand equations derived explicitly from consumer theory, there has been a continuing search for alternative specifications and functional forms. Many models have been proposed, but perhaps the most important in current use, apart from the ..."
Abstract - Cited by 636 (0 self) - Add to MetaCart
Ever since Richard Stone (1954) first estimated a system of demand equations derived explicitly from consumer theory, there has been a continuing search for alternative specifications and functional forms. Many models have been proposed, but perhaps the most important in current use, apart from

The Nuggetizer: Abstracting Away Higher-Orderness for Program Verification ⋆

by Paritosh Shroff, Christian Skalka, Scott F. Smith
"... Abstract. We develop a static analysis which distills first-order computational structure from higher-order functional programs. The analysis condenses higher-order programs into a first-order rule-based system, a nugget, that characterizes all value bindings that may arise from program execution. T ..."
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Abstract. We develop a static analysis which distills first-order computational structure from higher-order functional programs. The analysis condenses higher-order programs into a first-order rule-based system, a nugget, that characterizes all value bindings that may arise from program execution

A Theory of Diagnosis from First Principles

by Raymond Reiter - ARTIFICIAL INTELLIGENCE , 1987
"... Suppose one is given a description of a system, together with an observation of the system's behaviour which conflicts with the way the system is meant to behave. The diagnostic problem is to determine those components of the system which, when assumed to be functioning abnormally, will explain ..."
Abstract - Cited by 1120 (5 self) - Add to MetaCart
, will explain the discrepancy between the observed and correct system behaviour. We propose a general theory for this problem. The theory requires only that the system be described in a suitable logic. Moreover, there are many such suitable logics, e.g. first-order, temporal, dynamic, etc. As a result

Integrating classification and association rule mining

by Bing Liu, Wynne Hsu, Yiming Ma - In Proc of KDD , 1998
"... Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target of di ..."
Abstract - Cited by 578 (21 self) - Add to MetaCart
). An efficient algorithm is also given for building a classifier based on the set of discovered CARs. Experimental results show that the classifier built this way is, in general, more accurate than that produced by the state-of-the-art classification system C4.5. In addition, this integration helps to solve a

The ordinal numbers

by Grzegorz Bancerek - Journal of Formalized Mathematics , 1989
"... Summary. We present the choice function rule in the beginning of the article. In the main part of the article we formalize the base of cardinal theory. In the first section we introduce the concept of cardinal numbers and order relations between them. We present here Cantor-Bernstein theorem and oth ..."
Abstract - Cited by 731 (68 self) - Add to MetaCart
Summary. We present the choice function rule in the beginning of the article. In the main part of the article we formalize the base of cardinal theory. In the first section we introduce the concept of cardinal numbers and order relations between them. We present here Cantor-Bernstein theorem

Randomized kinodynamic planning

by Steven M. Lavalle, James J. Kuffner, Jr. - THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378 , 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
Abstract - Cited by 626 (35 self) - Add to MetaCart
space that has both first-order differential constraints and obstaclebased global constraints. The state space serves the same role as the configuration space for basic path planning; however, standard randomized path-planning techniques do not directly apply to planning trajectories in the state space
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