Notes Monographs & Edited Books Generally Accessible Papers My Favorite Publications (not necessarily yours) Selected Publications (besides my favorites) More Publications (+abstracts,BibTeX,pdf,slides,code,...)

Monographs & Edited Books

Notes

Generally Accessible Papers

• One Decade of Universal Artificial Intelligence
  In Theoretical Foundations of Artificial General Intelligence (2012) 67?--88?
  [gentle introduction, history, future, and discussion]
  
  
• Can Intelligence Explode?
  Journal of Consciousness Studies, 19:1-2 (2012) 143-166
  [some thoughts on the technological singularity]
  
  
• A Philosophical Treatise of Universal Induction (with S. Rathmanner)
  Entropy, 16:6 (2011) 1076-1136
  [philosophical, statistical, and computational foundations]
  
  
• Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence
  In Randomness through Computation (2011) 159--169
  [a personal account on the past and future for a general audience]
  
  
• A Complete Theory of Everything (will be subjective)
  Algorithms, 3:4 (2010) 329-350
  [importance of observer localization]
  
  
• Universal Intelligence: A Definition of Machine Intelligence (with S. Legg)
  Minds and Machines, 17:4 (2007) 391-444
  [a gentle non-mathematical introduction; recommended]
  
  
• Algorithmic Information Theory: a brief non-technical guide to the field
  Scholarpedia, 2:3 (2007) 2519
  [an extended encyclopedic entry; good coverage]
  
  

My Favorite Publications (not necessarily yours)

• Probabilities on Sentences in an Expressive Logic (with J.W. Lloyd & K.S. Ng & W.T.B. Uther)
  Technical Report (2012) http://arxiv.org/abs/1209.2620 [slides]
  [unifies probability and logic for learning]
  
  
• A Monte Carlo AIXI Approximation (with J. Veness & K. S. Ng & W. Uther & D. Silver)
  Journal of Artificial Intelligence Research, 40 (2011) 95-142
  [implementation of Universal AI. AIXI learns to play Poker,Pacman,TicTacToe,...]
  
  
• Feature Reinforcement Learning: Part I: Unstructured MDPs
  Journal of Artificial General Intelligence, 1 (2009) 3-24
  [my currently best bet towards practical universal AI; first runner-up for the Kurzweil best paper prize]
  
  
• On Universal Prediction and Bayesian Confirmation
  Theoretical Computer Science, 384:1 (2007) 33-48
  [solves the induction problem; recommended]
  
  
• Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability
  EATCS Book, Springer, Berlin (2005)
  [first complete and sound theory of AI]
  
  
• Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet
  Journal of Machine Learning Research 4 (2003) 971-1000
  [consistency and bounds for non-i.i.d. time-series prediction; very readable]
  
  
• Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures
  Proc. 15th Annual Conf. on Computational Learning Theory (COLT-2002) 364-379
  [the core proof of the optimality of the universal AIξ model]
  
  
• The Fastest and Shortest Algorithm for All Well-Defined Problems
  International Journal of Foundations of Computer Science, 13:3 (2002) 431-443
  [asymptotically true; my most popular paper]
  
  
• Family Structure from Periodic Solutions of an Improved Gap Equation (with A. Blumhofer)
  Nuclear Physics B484 (1997) 80-96; B494 (1997) 485
  [solves the mystery of quarks coming in families with exponential mass spectrum]
  
  

Selected Publications (besides my favorites)

• The Loss Rank Principle for Model Selection
  Proc. 20th Annual Conf. on Learning Theory (COLT-2007) 589-603
  [for (non)parametric non-stochastic regression and classification like kNN]
  
  
• Bayesian Regression of Piecewise Constant Functions
  Bayesian Statistics 8 (ISBA-2007) 607-612
  [Lindley prize for innovative research in Bayesian statistics]
  
  
• Fitness Uniform Optimization (with S. Legg)
  IEEE Transactions on Evolutionary Computation, 10:5 (2006) 568-589
  [a simple effective selection scheme with no explicit selection pressure]
  
  
• Asymptotics of Discrete MDL for Online Prediction (with J. Poland)
  IEEE Transactions on Information Theory, 51:11 (2005) 3780-3795
  [the Minimal Description Length principle for discrete model classes]
  
  
• Hybrid Rounding Techniques for Knapsack Problems (with M. Mastrolilli)
  Discrete Applied Mathematics, 154:4 (2006) 640--649
  [a linear!time algorithm for the knapsack problem]
  
  
• Adaptive Online Prediction by Following the Perturbed Leader (with J. Poland)
  Journal of Machine Learning Research 6 (2005) 639-660
  [elegant Sqrt(Loss) regret for general loss and adaptive learning rate]
  
  
• Distribution of Mutual Information from Complete and Incomplete Data (with M. Zaffalon)
  Computational Statistics & Data Analysis 48:3 (2005) 633-657
  [simple, fast, and useful expressions]
  
  
• Practical Robust Estimators under the Imprecise Dirichlet Model
  International Journal of Approximate Reasoning, 50:2 (2009) 231-242
  [simple, fast, and useful expressions]
  
  
• Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decisions
  Proc. 12th European Conf. on Machine Learning (ECML-2001) 226-238
  [first publication of the Universal AIXI model]
  
  
• Instantons in QCD: Theory and Application of the Instanton Liquid Model
  Ph.D. Thesis, LMU (1996), hep-ph/0107098
  [nice introduction with some new results, but nothing remarkable]
  
  

More Publications (+ abstracts, BibTeX, citations, ...)

• Long hyper-linked list of publications in my CV
• BibTeX with abstracts and links to papers, slides, code, latex, publisher, etc.
• Archived Publications in arXiv.org + latex & abstracts
• Listed at DBLP Bibliography Server + coauthor information
• Listed at Google Scholar + citation information
• Listed at Miscrosoft Academic Search + citation statistics
• Projects and Publications sorted w.r.t. topic
• Old publications in particle physics (QCD, Instantons)
• Outdates publications in computer graphics and others