Special Issue "Algorithmic Complexity"

Assistant Editor
Ms. Laura Simon
MDPI, Kandererstrasse 25, CH-4057 Basel, Switzerland
E-mail:

Guest Editor
Prof. Dr. Juergen Schmidhuber
IDSIA, Galleria 2, 6928 Manno-Lugano, Switzerland
Website: http://www.idsia.ch/~juergen/
E-mail:

Is the universe computable, as suggested in the 1940s by Konrad Zuse, inventor of the first working program-controlled computer? With the ascent of virtual realities the idea has become popular, and is now also being taken seriously by physicists, for lack of contrarian physical evidence. Questions to be addressed in this special issue include: Which kind of programs running on which type of computational device could in principle provide a concise description of quantum physics? How can algorithmic complexity theory guide the quest for simple explanations of the world in the sense of Occam's razor? How do Gödelian limits of mathematics and computation as well as insights from algorithmic complexity theory restrict the set of valid physical theories, including many world theories? Which sets of computable probability distributions or measures on possible universe histories make sense at all from the perspective of constructive mathematics? According to algorithmic information theory, how can the restrictions embodied by such sets help to predict future events, given past observations in a particular universe? Which testable predictions are made by algorithmic complexity-based theories of physics? Can we in principle design rational decision-making agents or artificial intelligences embedded in computable physics such that their decisions are optimal in reasonable mathematical senses? Which are the fundamental limitations of such decision makers?

Submission

All papers should be submitted to algorithms@mdpi.org. To be published continuously until the deadline and papers will be listed together at the special issue website.

Submitted papers should not have been published nor be under consideration for publication elsewhere. All papers are refereed through a peer-review process. A guide for authors is available on the Instructions for Authors page. Algorithms is an international peer-reviewed quarterly journal published by Molecular Diversity Preservation International.

Open Access publication fees are 300 CHF per paper. English correction fees and/or formatting fees (250 CHF) will be added in certain cases (550 CHF per paper for those papers that require extensive additional formatting and/or English corrections.).

Article Processing Charges (APC)

Article Processing Charges (APC) will be waived for well prepared manuscripts of invited papers. For the first two volumes of this new journal the APC are of 300 CHF (or 550 CHF per paper for those papers that require extensive additional formatting and/or English corrections).

algorithmic complexity, algorithmic information theory, Kolmogorov complexity, descriptive complexity, Kolmogorov-Chaitin complexity, stochastic complexity, algorithmic entropy, program-size complexity, Chaitin entropy, Chaitin complexity

Title: MML, Occam's razor, explanation, prediction, entropy, time's arrow, intelligent design and miracles
Author: David Dowe
Abstract: We introduce Minimum Message Length (MML) (Wallace & Boulton, 1968) as a statistically invariant and statistically consistent Bayesian interpretation of algorithmic information theory and Occam's razor. Despite problems of other approaches with retaining statistical consistency under model misspecification (Grunwald & Langford, 2007), no known evidence exists yet of a problem for MML here. We explore the frequently misunderstood distinction between inference (or induction, or explanation) and prediction. We then focus on Wallace's idea (2005) that, given CPT-invariance in Physics, it appears that - contrary to wide-held beliefs - entropy is not time's arrow. We then address why it is that people wish to predict the future but (only) infer (or explain) the past. We draw attention to MML's ability to predict better than rival methods while using simpler models, mentioning some areas of application in physical models. We offer some scepticism about quantum computing, and we use MML to address evidence of ``intelligent design'' (Dowe et al., 2009) and miracles (Dowe, 2008a).

Title: Open Problems in Universal Induction & Intelligence
Author: Marcus Hutter
Abstract: Specialized intelligent systems can be found everywhere: finger print, handwriting, speech, and face recognition, spam filtering, chess and other game programs, robots, et al. This decade the first presumably complete *mathematical* theory of artificial intelligence based on universal induction-prediction-decision-action has been proposed. This information-theoretic approach solidifies the foundations of inductive inference and artificial intelligence. Getting the foundations right usually marks a significant progress and maturing of a field. The theory provides a gold standard and guidance for researchers working on intelligent algorithms. The roots of universal induction have been laid exactly half-a-century ago; the roots of universal intelligence exactly one decade ago. So it is timely to take stock of what has been achieved and what remains to be done. Since there are already good recent surveys, we describe the state-of-the-art only in passing and refer
the reader to literature. This article concentrates on the open problems in universal induction and its extension to universal intelligence.