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 / David L. Dowe (eds.)
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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Full Text (via Springer) |
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| Format: | Conference Proceeding eBook |
| Language: | English |
| Published: |
Heidelberg :
Springer,
2013.
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| Series: | Lecture notes in computer science ;
7070. LNCS sublibrary. Theoretical computer science and general issues. Lecture notes in computer science. Lecture notes in artificial intelligence. |
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Table of Contents:
- Introduction. Introduction to Ray Solomonoff 85th Memorial Conference / David L. Dowe
- Invited Papers. Ray Solomonoff and the New Probability / Grace Solomonoff
- Universal Heuristics: How Do Humans Solve "Unsolvable" Problems? / Leonid A. Levin
- Partial Match Distance / Ming Li
- Long Papers. Falsification and Future Performance / David Balduzzi
- The Semimeasure Property of Algorithmic Probability
- "Feature" or "Bug"? / Douglas Campbell
- Inductive Inference and Partition Exchangeability in Classification / Jukka Corander, Yaqiong Cui and Timo Koski
- Learning in the Limit: A Mutational and Adaptive Approach / Reginaldo Inojosa da Silva Filho and Ricardo Luis de Azevedo da Rocha
- Algorithmic Simplicity and Relevance / Jean-Louis Dessalles
- Categorisation as Topographic Mapping between Uncorrelated Spaces / T. Mark Ellison
- Algorithmic Information Theory and Computational Complexity / Rūsiņš Freivalds
- A Critical Survey of Some Competing Accounts of Concrete Digital Computation / Nir Fresco
- Further Reflections on the Timescale of AI / J. Storrs Hall
- Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL / Bing Hu [and others]
- Complexity Measures for Meta-learning and Their Optimality / Norbert Jankowski
- Design of a Conscious Machine / P. Allen King
- No Free Lunch versus Occam's Razor in Supervised Learning / Tor Lattimore and Marcus Hutter
- An Approximation of the Universal Intelligence Measure / Shane Legg and Joel Veness
- Minimum Message Length Analysis of the Behrens-Fisher Problem / Enes Makalic and Daniel F. Schmidt
- MMLD Inference of Multilayer Perceptrons / Enes Makalic and Lloyd Allison
- An Optimal Superfarthingale and Its Convergence over a Computable Topological Space / Kenshi Miyabe
- Diverse Consequences of Algorithmic Probability / Eray Özkural
- An Adaptive Compression Algorithm in a Deterministic World / Kristiaan Pelckmans
- Toward an Algorithmic Metaphysics / Steve Petersen
- Limiting Context by Using the Web to Minimize Conceptual Jump Size / Rafal Rzepka, Koichi Muramoto and Kenji Araki
- Minimum Message Length Order Selection and Parameter Estimation of Moving Average Models / Daniel F. Schmidt
- Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction / Adrian Silvescu and Vasant Honavar
- Locating a Discontinuity in a Piecewise-Smooth Periodic Function Using Bayes Estimation / Alex Solomonoff
- On the Application of Algorithmic Probability to Autoregressive Models / Ray J. Solomonoff and Elias G. Saleeby
- Principles of Solomonoff Induction and AIXI / Peter Sunehag and Marcus Hutter
- MDL/Bayesian Criteria Based on Universal Coding/Measure / Joe Suzuki
- Algorithmic Analogies to Kamae-Weiss Theorem on Normal Numbers / Hayato Takahashi
- (Non- )Equivalence of Universal Priors / Ian Wood, Peter Sunehag and Marcus Hutter
- A Syntactic Approach to Prediction / John Woodward and Jerry Swan
- Short Paper. Developing Machine Intelligence within P2P Networks Using a Distributed Associative Memory / Amiza Amir, Anang Hudaya M. Amin and Asad Khan.