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An Introduction to Universal Artificial Intelligence

Af: Marcus Hutter, Elliot Catt, David Quarel Engelsk Paperback

An Introduction to Universal Artificial Intelligence

Af: Marcus Hutter, Elliot Catt, David Quarel Engelsk Paperback
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An Introduction to Universal Artificial Intelligence provides the formal underpinning of what it means for an agent to act intelligently in an unknown environment. First presented in Universal Algorithmic Intelligence (Hutter, 2000), UAI offers a framework in which virtually all AI problems can be formulated, and a theory of how to solve them. UAI unifies ideas from sequential decision theory, Bayesian inference, and algorithmic information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI is the theoretical gold standard for intelligent behavior.

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. You can also visit the author website: http://www.hutter1.net/ai/uaibook2.htm.

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An Introduction to Universal Artificial Intelligence provides the formal underpinning of what it means for an agent to act intelligently in an unknown environment. First presented in Universal Algorithmic Intelligence (Hutter, 2000), UAI offers a framework in which virtually all AI problems can be formulated, and a theory of how to solve them. UAI unifies ideas from sequential decision theory, Bayesian inference, and algorithmic information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI is the theoretical gold standard for intelligent behavior.

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. You can also visit the author website: http://www.hutter1.net/ai/uaibook2.htm.

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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 516
ISBN-13: 9781032607023
Indbinding: Paperback
Udgave:
ISBN-10: 1032607025
Kategori: Robotteknik
Udg. Dato: 28 maj 2024
Længde: 27mm
Bredde: 254mm
Højde: 176mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 28 maj 2024
Forfatter(e): Marcus Hutter, Elliot Catt, David Quarel
Forfatter(e) Marcus Hutter, Elliot Catt, David Quarel

Kategori Robotteknik

ISBN-13 9781032607023

Sprog Engelsk

Indbinding Paperback

Sider 516

Udgave

Længde 27mm

Bredde 254mm

Højde 176mm

Udg. Dato 28 maj 2024

Oplagsdato 28 maj 2024

Forlag Taylor & Francis Ltd

Kategori sammenhænge