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Authors: Marcus Hutter and David Quarel and Elliot Catt

Publisher: Chapman & Hall, ISBN: 9781032607023, DOI: TBA

Date: © May 2024, Pages: 500

The book can be ordered from routledge.com, or amazon.com / co.uk / de / or most other bookshops.

The book covers both the theoretical and practical aspects of UAI. Bayesian updating can be done efficiently with context tree weighting, and planning can be approximated by sampling with Monte Carlo tree search. It provides algorithms for the reader to implement, and experimental results to compare against. These algorithms are used to approximate AIXI. The book ends with a philosophical discussion of Artificial General Intelligence: Can super-intelligent agents even be constructed? Is it inevitable that they will be constructed, and what are the potential consequences?

This text is suitable for late undergraduate students. It provides an extensive chapter to fill in the required mathematics, probability, information, and computability theory background.

The book is

- Part I: Introduction
- Part II: Algorithmic Prediction
- Part III: A Family of Universal Agents
- Part IV: Approximating Universal Agents
- Part V: Alternative Approaches
- Part VI: Safety and Discussion

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“This is seminal work!”

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“This is an important, timely, high-quality book by highly respected authors.”

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“Clearly very strongly based on mathematical foundations. This offers a theoretical depth which will be of value in research, education (at an appropriate level), and for advanced practitioners.”

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- Errors and typos
- Simplified proofs or improved results
- LaTeXed solutions to exercises
- An illustration, example, remark, exercise, or (better) explanation
- New content if you feel it is missing (though the bar is probably high)

Your suggestions will be considered for the next edition/printing or a potential future online version.

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