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30
Optimal Composition of RealTime Systems
 ARTIFICIAL INTELLIGENCE
, 1996
"... Realtime systems are designed for environments in which the utility of actions is strongly timedependent. Recent work by Dean, Horvitz and others has shown that anytime algorithms are a useful tool for realtime system design, since they allow computation time to be traded for decision quality. In ..."
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Cited by 113 (21 self)
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Realtime systems are designed for environments in which the utility of actions is strongly timedependent. Recent work by Dean, Horvitz and others has shown that anytime algorithms are a useful tool for realtime system design, since they allow computation time to be traded for decision quality. In order to construct complex systems, however, we need to be able to compose larger systems from smaller, reusable anytime modules. This paper addresses two basic problems associated with composition: how to ensure the interruptibility of the composed system
Computations with Imprecise Parameters in Engineering Design: Background and Theory
 ASME JOURNAL OF MECHANISMS, TRANSMISSIONS, AND AUTOMATION IN DESIGN
, 1989
"... A technique to perform design calculations on imprecise representations of parameters has been developed and is presented. The level of imprecision in the description of design elements is typically high in the preliminary phase of engineering design. This imprecision is represented using the fuzzy ..."
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Cited by 53 (18 self)
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A technique to perform design calculations on imprecise representations of parameters has been developed and is presented. The level of imprecision in the description of design elements is typically high in the preliminary phase of engineering design. This imprecision is represented using the fuzzy calculus. Calculations can be performed using this method, to produce (imprecise) performance parameters from imprecise (input) design parameters. The Fuzzy Weighted Average technique is used to perform these calculations. A new metric, called the γlevel measure, is introduced to determine the relative coupling between imprecise inputs and outputs. The background and theory supporting this approach are presented, along with one example.
Measurement Of Membership Functions: Theoretical And Empirical Work
, 1995
"... This chapter presents a review of various interpretations of the fuzzy membership function together with ways of obtaining a membership function. We emphasize that different interpretations of the membership function call for different elicitation methods. We try to make this distinction clear u ..."
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Cited by 21 (1 self)
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This chapter presents a review of various interpretations of the fuzzy membership function together with ways of obtaining a membership function. We emphasize that different interpretations of the membership function call for different elicitation methods. We try to make this distinction clear using techniques from measurement theory.
On Triangular NormBased Propositional Fuzzy Logics
 Fuzzy Sets and Systems
, 1995
"... Fuzzy logics based on triangular norms and their corresponding conorms are investigated. An affirmative answer to the question whether in such logics a specific level of satisfiability of a set of formulas can be characterized by the same level of satisfiability of its finite subsets is given. T ..."
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Cited by 16 (3 self)
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Fuzzy logics based on triangular norms and their corresponding conorms are investigated. An affirmative answer to the question whether in such logics a specific level of satisfiability of a set of formulas can be characterized by the same level of satisfiability of its finite subsets is given. Tautologies, contradictions and contingencies with respect to such fuzzy logics are studied, in particular for the important cases of minmax and Lukasiewicz logics. Finally, fundamental tnormbased fuzzy logics are shown to provide a gradual transition between minmax and Lukasiewicz logics. Key words: Fuzzy Logics, Minmax logic, Lukasiewicz Logic, Triangular Norms, Satisfiability. AMSClassification: 03B52, 03B50, 03B05 0
Bayesian Network Modelling through Qualitative Patterns
 ARTIFICIAL INTELLIGENCE
, 2003
"... In designing a Bayesian network for an actual problem, developers need to bridge the gap between the mathematical abstractions o#ered by the Bayesiannetwork formalism and the features of the problem to be modelled. Qualitative probabilistic networks (QPNs) have been put forward as qualitative an ..."
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Cited by 12 (5 self)
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In designing a Bayesian network for an actual problem, developers need to bridge the gap between the mathematical abstractions o#ered by the Bayesiannetwork formalism and the features of the problem to be modelled. Qualitative probabilistic networks (QPNs) have been put forward as qualitative analogues to Bayesian networks, and allow modelling interactions in terms of qualitative signs. They thus have the advantage that developers can abstract from the numerical detail, and therefore the gap may not be as wide as for their quantitative counterparts. A notion that has been suggested in the literature to facilitate Bayesiannetwork development is causal independence. It allows exploiting compact representations of probabilistic interactions among variables in a network. In the paper, we deploy both causal independence and QPNs in developing and analysing a collection of qualitative, causal interaction patterns, called QC patterns. These are endowed with a fixed qualitative semantics, and are intended to o#er developers a highlevel starting point when developing Bayesian networks.
Symbolic Artificial Intelligence And Numeric Artificial Neural Networks: Towards A Resolution Of The Dichotomy
 In: Computational Architectures Integrating Symbolic and Neural
, 1994
"... This memory can take several forms based on the time scales at which such modifications are allowed. Some symbol structures might have the property of determining choice and the order of application of transformations to be applied on other symbol structures. These are essentially the programs. Prog ..."
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Cited by 8 (3 self)
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This memory can take several forms based on the time scales at which such modifications are allowed. Some symbol structures might have the property of determining choice and the order of application of transformations to be applied on other symbol structures. These are essentially the programs. Programs when executed  typically through the conventional process of compilation and interpretation and eventually  when they operate on symbols that are linked through grounding to particular effectors  produce behavior. Working memory holds symbol structures as they are being processed. Longterm memory, generally speaking, is the repository of programs and can be changed by addition, deletion, or modification of symbol structures that it holds. Such a system can compute any Turingcomputable function provided it has sufficiently large memory and its primitive set of transformations are adequate for the composition of arbitrarily symbol structures (programs) and the interpreter is capable of interpreting any possible symbol structure. This also means that any particular set of symbolic processes can be carried out by an NANN  provided it has potentially infinite memory, or finds a way to use its transducers and effectors to use the external physical environment to serve as its memory). 14 Chapter 12 Knowledge in SAI systems is typically embedded in complex symbol structures such as lists (Norvig, 1992), logical databases (Genesereth and Nilsson, 1987), semantic networks (Quillian, 1968), frames (Minsky, 1975), schemas (Arbib, 1972; 1994), and manipulated by (often serial) procedures or inferences (e.g., list processing, application of production rules (Waterman, 1985), or execution of logic programs (Kowalski, 1977) carried out by a central processor that accesse...
Mapping Bayesian Networks to Stochastic Neural Networks: A Foundation for Hybrid BayesianNeural Systems
, 1995
"... In this work, we are interested in the problem of finding maximum a posteriori probability (MAP) value assignments for a set of discrete attributes, given the constraint that some of the attributes are permanently fixed to some values a priori. For building a system capable of this type of uncertain ..."
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Cited by 6 (2 self)
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In this work, we are interested in the problem of finding maximum a posteriori probability (MAP) value assignments for a set of discrete attributes, given the constraint that some of the attributes are permanently fixed to some values a priori. For building a system capable of this type of uncertain reasoning in practice, we need first to construct an accurate abstract representation of the problem domain, and then to establish an efficient search mechanism for finding MAP configurations within the constructed model. We propose a hybrid Bayesian networkneural network system for solving these two subtasks. The Bayesian network component can be used for constructing a compact, highlevel representation for the problem domain probability distribution quickly and reliably, assuming that suitable expert knowledge is available. The neural network component provides then a computationally efficient, massively parallel platform for searching the model state space. The main application areas f...
On Very True
"... The fuzzy truth value "very true" is formalized as a unary connective (hedge). A complete axiomatization is presented. ..."
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Cited by 2 (0 self)
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The fuzzy truth value "very true" is formalized as a unary connective (hedge). A complete axiomatization is presented.
Fuzzy control as a fuzzy deduction system
, 2001
"... An approach to fuzzy control based on fuzzy logic in narrow sense (fuzzy inference rules + fuzzy set of logical axioms) is proposed. This gives an interesting theoretical framework and suggests new tools for fuzzy control. ..."
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Cited by 2 (1 self)
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An approach to fuzzy control based on fuzzy logic in narrow sense (fuzzy inference rules + fuzzy set of logical axioms) is proposed. This gives an interesting theoretical framework and suggests new tools for fuzzy control.