Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30 -- December 2, 2011 /

Algorithmic probability and friends: Proceedings of the Ray Solomonoff 85th memorial conference is a collection of original work and surveys. The Solomonoff 85th memorial conference was held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff (1...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Dowe, David L. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Lecture Notes in Artificial Intelligence, 7070
Temas:
Computer science.
Computer Science.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction to Ray Solomonoff 85th Memorial Conference
  • Ray Solomonoff and the New Probability
  • Universal Heuristics: How Do Humans Solve "Unsolvable" Problems?
  • Partial Match Distance
  • Falsification and Future Performance
  • The Semimeasure Property of Algorithmic Probability - "Feature" or "Bug"?
  • Inductive Inference and Partition Exchangeability in Classification
  • Learning in the Limit: A Mutational and Adaptive Approach
  • Algorithmic Simplicity and Relevance
  • Categorisation as Topographic Mapping between Uncorrelated Spaces
  • Algorithmic Information Theory and Computational Complexity
  • A Critical Survey of Some Competing Accounts of Concrete Digital Computation
  • Further Reflections on the Timescale of AI
  • Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL
  • Complexity Measures for Meta-learning and Their Optimality
  • Design of a Conscious Machine
  • No Free Lunch versus Occam's Razor in Supervised Learning
  • An Approximation of the Universal Intelligence Measure
  • Minimum Message Length Analysis of the Behrens-Fisher Problem
  • MMLD Inference of Multilayer Perceptrons
  • An Optimal Superfarthingale and Its Convergence over a Computable Topological Space
  • Diverse Consequences of Algorithmic Probability
  • An Adaptive Compression Algorithm in a Deterministic World
  • Toward an Algorithmic Metaphysics
  • Limiting Context by Using the Web to Minimize Conceptual Jump Size
  • Minimum Message Length Order Selection and Parameter Estimation of Moving Average Models
  • Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction
  • Locating a Discontinuity in a Piecewise-Smooth Periodic Function Using Bayes Estimation
  • On the Application of Algorithmic Probability to Autoregressive Models
  • Principles of Solomonoff Induction and AIXI
  • MDL/Bayesian Criteria Based on Universal Coding/Measure
  • Algorithmic Analogies to Kamae-Weiss Theorem on Normal Numbers
  • (Non-)Equivalence of Universal Priors
  • A Syntactic Approach to Prediction
  • Developing Machine Intelligence within P2P Networks Using a Distributed Associative Memory.  .

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