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    1. Data och IT
    2. Systemvetenskap och AI
    3. Artificiell intelligens

    Constraint Programming and Decision Making

    AvMartine Ceberio,Vladik Kreinovich

    Häftad, Engelska, 2016

    Del i serien Studies in Computational Intelligence

    1 116 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    In many application areas, it is necessary to make effective decisions under constraints. Several area-specific techniques are known for such decision problems; however, because these techniques are area-specific, it is not easy to apply each technique to other applications areas. Cross-fertilization between different application areas is one of the main objectives of the annual International Workshops on Constraint Programming and Decision Making. Those workshops, held in the US (El Paso, Texas), in Europe (Lyon, France) and in Asia (Novosibirsk, Russia), from 2008 to 2012, have attracted researchers and practitioners from all over the world. This volume presents extended versions of selected papers from those workshops. These papers deal with all stages of decision making under constraints: (1) formulating the problem of multi-criteria decision making in precise terms, (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms and making these algorithms as efficient as possible and (4) taking into account interval, probabilistic and fuzzy uncertainty inherent in the corresponding decision making problems. The resulting application areas include environmental studies (selecting the best location for a meteorological tower), biology (selecting the most probable evolution history of a species), and engineering (designing the best control for a magnetic levitation train).

    Produktinformation

    • Utgivningsdatum:2016-08-27
    • Mått:155 x 235 x 13 mm
    • Vikt:347 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Studies in Computational Intelligence
    • Antal sidor:209
    • Förlag:Springer International Publishing AG
    • ISBN:9783319382029

    Utforska kategorier

    • Artificiell intelligens inom Data och IT

    Innehållsförteckning

    • Algorithmics of Checking Whether a Mapping Is Injective, Surjective,and/or Bijective.-Simplicity Is Worse Than Theft: A Constraint-Based Explanation of aSeemingly Counter-Intuitive Russian Saying.-Continuous If-Then Statements Are Computable.-Linear programming with Interval Type-2 fuzzy constraints.-Epistemic Considerations on Expert Disagreement, NormativeJustification, and Inconsistency Regarding Multi-Criteria Decision Making .-Interval Linear Programming Techniques in Constraint Programmingand Global Optimization.-Selecting the Best Location for a Meteorological Tower: A Case Studyof Multi-Objective Constraint Optimization.-Gibbs Sampling as a Natural Statistical Analog of ConstraintsTechniques: Prediction in Science under General Probabilistic Uncertainty .-Why Tensors.-Adding Constraints – A (Seemingly Counterintuitive but) UsefulHeuristic in Solving Difficult Problems.-Under Physics-Motivated Constraints, Generally-Non-Algorithmic Computational Problems Become Algorithmically Solvable.-Constraint-Related Reinterpretation of Fundamental PhysicalEquations Can Serve as a Built-In Regularization.-Optimization of the Choquet Integral using Genetic Algorithm .-Optimization of the Choquet Integral using Genetic Algorithm .-Scalable, Portable, Verifiable Kronecker Products on Multi-ScaleComputers.-Reliable and Robust Synthesis of QFT controller using ICSP.-Towards an Efficient Bisection of Ellipsoids .-.-An Auto-validating Rejection Sampler for Differentiable ArithmeticalExpressions: Posterior Sampling of Phylogenetic Quartets.-Graph Subdivision Methods in Interval Global Optimization .-An Extended BDI-Based Model for Human Decision-Making and SocialBehavior: Various Applications .-Why Curvature in L-Curve: Combining Soft Constraints .-Surrogate Models for Mixed Discrete-Continuous Variables Why Ellipsoid Constraints, Ellipsoid Clusters, and RiemannianSpace-Time: Dvoretzky’s Theorem Revisited