Real-time systems are designed for environments in which the utility of actions is strongly time-dependent. Recent work by Dean, Horvitz and others has shown that anytime algorithms are a useful tool for real-time 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

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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 γ-level 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. 1.

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.

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 min-max and Lukasiewicz logics. Finally, fundamental t-norm-based fuzzy logics are shown to provide a gradual transition between minmax and Lukasiewicz logics. Key words: Fuzzy Logics, Min-max logic, Lukasiewicz Logic, Triangular Norms, Satisfiability. AMS-Classification: 03B52, 03B50, 03B05 0

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. Long-term 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 Turing-computable 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...

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 network-neural network system for solving these two subtasks. The Bayesian network component can be used for constructing a compact, high-level 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...

The fuzzy truth value "very true" is formalized as a unary connective (hedge). A complete axiomatization is presented.

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. Long--term memory, generally speaking, is the repository of programs and can be changed by addition, deletion, or modification of symbol structures that it holds. The reader is refered to (Newell, 1990) for a detailed treatment of symbol systems of this sort. Such a symbol system can compute any Turing--computable function provided it has sufficiently large memory and its primitive set of transformations are Beyond Symbolic AI and Connectionist Networks 7 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 a CN -- provided it has potentially infinite memory, or finds a way to use its transducers and effectors to use the external physical environment to augment its memory (just as humans have in their use of stone tablets, papyrus, and books through the ages). 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 mani...

Abstract. Logics for ‘generally ’ were introduced for handling assertions with vague notions, such as ‘generally’, ‘most’, ‘several’, etc., by generalized quantifiers, ultrafilter logic being an interesting case. Here, we show that ultrafilter logic can be faithfully embedded into a first-order theory of certain functions, called coherent. We also use generic functions (akin to Skolem functions) to enable elimination of the generalized quantifier. These devices permit using methods for classical first-order logic to reason about consequence in ultrafilter logic.