The book?provides a gentle introduction to Universal Artificial Intelligence (UAI), a theory that provides a formal underpinning of what it means for an agent to act intelligently in a general class of environments.?
Part I: Introduction. 1. Introduction. 2. Background. Part II: Algorithmic Prediction. 3. Bayesian Sequence Prediction. 4. The Context Tree Weighting Algorithm. 5. Variations on CTW.?Part III: A Family of Universal Agents. 6.?Agency. 7. Universal Artificial Intelligence. 8. Optimality of Universal Agents. 9. Other Universal Agents. 10. Multi-agent Setting.?Part IV: Approximating Universal Agents. 11.?AIXI-MDP. 12. Monte-Carlo AIXI with Context Tree Weighting. 13. Computational Aspects.?Part V: Alternative Approaches. 14.?Feature Reinforcement Learning.?Part VI: Safety and Discussion. 15.?AGI Safety. 16. Philosophy of AI.?
Is it possible to mathematically define and study artificial superintelligence? If that sounds like an interesting question, then this is definitely the book for you. Starting with probability theory, complexity theory and sequence prediction, it takes you right through to the safety of superintelligent machines.
Shane Legg, co-founder of DeepMind
This is seminal work!
Roman Yampolskiy, Tenured Associate Professor at the University of Louisville, USA
This is an important, timely, high-quality book by highly respected authors.
J?rgen Schmidhuber, Director of the AI Initiative at King Abdullah University of Science and Technology, Scientific Director at the Swiss AI Lab IDSIA, Co-Founder & Chil#