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SemiringBased Constraint Satisfaction and Optimization
 JOURNAL OF THE ACM
, 1997
"... We introduce a general framework for constraint satisfaction and optimization where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. The framework is based on a semiring structure, where the set of the semiring specifies the values to be asso ..."
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Cited by 159 (20 self)
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We introduce a general framework for constraint satisfaction and optimization where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. The framework is based on a semiring structure, where the set of the semiring specifies the values to be associated with each tuple of values of the variable domain, and the two semiring operations (1 and 3) model constraint projection and combination respectively. Local consistency algorithms, as usually used for classical CSPs, can be exploited in this general framework as well, provided that certain conditions on the semiring operations are satisfied. We then show how this framework can be used to model both old and new constraint solving and optimization schemes, thus allowing one to both formally justify many informally taken choices in existing schemes, and to prove that local consistency techniques can be used also in newly defined schemes.
Bidirectional Associative Memories
 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS
, 1988
"... Stability and encoding properties of twolayer nonlinear feedback neural networks are examined. Bidirectionality, forward and backard information flow, is introduced in neural nets to produce twoway associative search for stored associations (A, B, ). Passing information through M gives one directi ..."
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Cited by 157 (3 self)
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Stability and encoding properties of twolayer nonlinear feedback neural networks are examined. Bidirectionality, forward and backard information flow, is introduced in neural nets to produce twoway associative search for stored associations (A, B, ). Passing information through M gives one direction; passing it through its transpose M r gives the other. A bidirectional associative memory. (BAM) behaves as a hetero associative content addressable memory (CAM), storing and recalling the vector pairs (A1, Bi),..,(Am Bin) , where .4 {0,1}"and B We prove that every nbyp matrix M is a bidirectionally stable heteroas sociative CAM for both binary/bipolar and continuous neurons a, and hi. When the BAM neurons are activated, the network quickly evolves to a stable state of twopattern reverberation, or resonance. The stable reverberation corresponds to a system energy local minimum. Heteroassociafive inlormation is encoded iu a BAM by summing correlation matrices. The BAM storage capact .ty for reliable recall is roughly m < niin(n, p). No more heteroassociafive pairs can be 'reliably stored and recalled than the lesser of the dimensions of the pattern spaces (0,1 }"and 0,1 } P. The Appendix shos that it is better on average to use bipolar { 1,i} coding than binary. {0,1 } coding of heteroassociative pairs (.4, B,). BAM encoding and decoding are combined in the adaptive BAM, which extends global bidirectional stabflit), to realtime unsupervised learning. Temporal patterns (AE,., A,,) are represented as ordered lists of binary/bipolar vectors and stored in a temporal associative memory (TAM) nby matrix M as a limit cycle of the dynamical system. Forward recall proceeds through M, backward recall through M r . Temporal patterns are stored by summing contiguous bipolar...
Neurofuzzy modeling and control
 IEEE Proceedings
, 1995
"... Abstract  Fundamental and advanced developments in neurofuzzy synergisms for modeling and control are reviewed. The essential part of neurofuzzy synergisms comes from a common framework called adaptive networks, which uni es both neural networks and fuzzy models. The fuzzy models under the framew ..."
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Cited by 150 (1 self)
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Abstract  Fundamental and advanced developments in neurofuzzy synergisms for modeling and control are reviewed. The essential part of neurofuzzy synergisms comes from a common framework called adaptive networks, which uni es both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called ANFIS (AdaptiveNetworkbased Fuzzy Inference System), which possess certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neurofuzzy approaches are also addressed. KeywordsFuzzy logic, neural networks, fuzzy modeling, neurofuzzy modeling, neurofuzzy control, ANFIS. I.
Autopilot: Adaptive control of distributed applications
 In HPDC
"... With increasing development of applications for heterogeneous, distributed computing grids, the focus of performance analysis has shifted from a posteriori optimization on homogeneous parallel systems to application tuning for heterogeneous resources with time varying availability. This shift has pr ..."
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Cited by 135 (11 self)
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With increasing development of applications for heterogeneous, distributed computing grids, the focus of performance analysis has shifted from a posteriori optimization on homogeneous parallel systems to application tuning for heterogeneous resources with time varying availability. This shift has profound implications for performance instrumentation and analysis techniques. Autopilot is a new infrastructure for dynamic performance tuning of heterogeneous computational grids based on closed loop control. This paper describes the Autopilot model of distributed sensors, actuators, and decision procedures, reports preliminary performance benchmarks, and presents a case study in which the Autopilot library is utilized in the development of an adaptive parallel input/output system. 1.
Probabilistic Logic Programming
, 1992
"... Of all scientific investigations into reasoning with uncertainty and chance, probability theory is perhaps the best understood paradigm. Nevertheless, all studies conducted thus far into the semantics of quantitative logic programming (cf. van Emden [51], Fitting [18, 19, 20], Blair and Subrahmanian ..."
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Cited by 133 (7 self)
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Of all scientific investigations into reasoning with uncertainty and chance, probability theory is perhaps the best understood paradigm. Nevertheless, all studies conducted thus far into the semantics of quantitative logic programming (cf. van Emden [51], Fitting [18, 19, 20], Blair and Subrahmanian [5, 6, 49, 50], Kifer et al [29, 30, 31]) have restricted themselves to nonprobabilistic semantical characterizations. In this paper, we take a few steps towards rectifying this situation. We define a logic programming language that is syntactically similar to the annotated logics of [5, 6], but in which the truth values are interpreted probabilistically. A probabilistic model theory and fixpoint theory is developed for such programs. This probabilistic model theory satisfies the requirements proposed by Fenstad [16] for a function to be called probabilistic. The logical treatment of probabilities is complicated by two facts: first, that the connectives cannot be interpreted truth function...
Fuzzy Queries in Multimedia Database Systems
, 1998
"... There are essential differences between multimedia databases (which may contain complicated objects, such as images), and traditional databases. These differences lead to interesting new issues, and in particular cause us to consider new types of queries. For example, in a multimedia database it is ..."
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Cited by 123 (1 self)
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There are essential differences between multimedia databases (which may contain complicated objects, such as images), and traditional databases. These differences lead to interesting new issues, and in particular cause us to consider new types of queries. For example, in a multimedia database it is reasonable and natural to ask for images that are somehow "similar to" some fixed image. Furthermore, there are different ways of obtaining and accessing information in a multimedia database than information in a traditional database. For example, in a multimedia database, it might be reasonable to have a query that asks for, say, the top 10 images that are similar to a fixed image. This is in contrast to a relational database, where the answer to a query is simply a set. (Of course, in a relational database, the result to a query may be sorted in some way for convenience in presentation, such as sorting department members by salary, but logically speaking, the result is still simply a set, ...
Minimal Probing: Supporting Expensive Predicates for Topk Queries
 In SIGMOD
, 2002
"... This paper addresses the problem of evaluating ranked top queries with expensive predicates. As major DBMSs now all support expensive userdefined predicates for Boolean queries, we believe such support for ranked queries will be even more important: First, ranked queries often need to model use ..."
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Cited by 119 (6 self)
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This paper addresses the problem of evaluating ranked top queries with expensive predicates. As major DBMSs now all support expensive userdefined predicates for Boolean queries, we believe such support for ranked queries will be even more important: First, ranked queries often need to model userspecific concepts of preference, relevance, or similarity, which call for dynamic userdefined functions. Second, middleware systems must incorporate external predicates for integrating autonomous sources typically accessible only by perobject queries. Third, fuzzy joins are inherently expensive, as they are essentially userdefined operations that dynamically associate multiple relations. These predicates, being dynamically defined or externally accessed, cannot rely on index mechanisms to provide zerotime sorted output, and must instead require perobject probe to evaluate. The current standard sortmerge framework for ranked queries cannot efficiently handle such predicates because it must completely probe all objects, before sorting and merging them to produce top answers. To minimize expensive probes, we thus develop the formal principle of "necessary probes," which determines if a probe is absolutely required. We then propose Algorithm MPro which, by implementing the principle, is provably optimal with minimal probe cost. Further, we show that MPro can scale well and can be easily parallelized. Our experiments using both a realestate benchmark database and synthetic datasets show that MPro enables significant probe reduction, which can be orders of magnitude faster than the standard scheme using complete probing.
A Multivalued Logic Approach to Integrating Planning and Control
 Artificial Intelligence
, 1995
"... Intelligent agents embedded in a dynamic, uncertain environment should incorporate capabilities for both planned and reactive behavior. Many current solutions to this dual need focus on one aspect, and treat the other one as secondary. We propose an approach for integrating planning and control base ..."
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Cited by 106 (8 self)
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Intelligent agents embedded in a dynamic, uncertain environment should incorporate capabilities for both planned and reactive behavior. Many current solutions to this dual need focus on one aspect, and treat the other one as secondary. We propose an approach for integrating planning and control based on behavior schemas, which link physical movements to abstract action descriptions. Behavior schemas describe behaviors of an agent, expressed as trajectories of control actions in an environment, and goals can be defined as predicates on these trajectories. Goals and behaviors can be combined to produce conjoint goals and complex controls. The ability of multivalued logics to represent graded preferences allows us to formulate tradeoffs in the combination. Two composition theorems relate complex controls to complex goals, and provide the key to using standard knowledgebased deliberation techniques to generate complex controllers. We report experiments in planning and execution on a mobi...
A fuzzy description logic for the semantic web
 Fuzzy Logic and the Semantic Web. Capturing Intelligence, Elsevier (2006) 73–90
"... Abstract. In this paper we present a fuzzy version of SHOIN (D), the corresponding ..."
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Cited by 103 (22 self)
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Abstract. In this paper we present a fuzzy version of SHOIN (D), the corresponding