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商品描述
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.
商品描述(中文翻譯)
《通用人工智慧入門》提供了一個正式的基礎，解釋了代理人在未知環境中如何以智能方式行動。該概念最初在《通用演算法智能》（Hutter, 2000）中提出，通用人工智慧提供了一個框架，幾乎可以解決所有人工智慧問題，並提供了解決這些問題的理論。通用人工智慧結合了順序決策理論、貝葉斯推論和演算法資訊理論的思想，構建了AIXI，一個在未知環境中學習以最佳方式行動的最優強化學習代理人。AIXI是智能行為的理論黃金標準。
該書涵蓋了通用人工智慧的理論和實踐兩個方面。可以使用上下文樹加權進行高效的貝葉斯更新，並可以使用蒙特卡羅樹搜索進行規劃的近似。它提供了讀者實施算法的指南，並提供了實驗結果進行比較。這些算法用於近似AIXI。該書以哲學討論人工通用智能結束：超智能代理人是否可以建構？它們是否不可避免地會被建構，並且可能產生什麼後果？
這本書適合高年級本科生閱讀。它提供了一個詳細的章節，填補了所需的數學、概率、信息和可計算性理論背景知識。
作者簡介
Marcus Hutter is Senior Researcher at DeepMind in London and Professor in the Research School of Computer Science (RSCS) at the Australian National University (ANU) in Canberra, Australia (fulltime till 2019 and honorary since then). He is Chair of the ongoing Human Knowledge Compression Contest. He received a master's degree in computer science in 1992 from the University of Technology in Munich, Germany, a PhD in theoretical particle physics in 1996, and completed his Habilitation in 2003. He worked as an active software developer for various companies in several areas for many years, before he commenced his academic career in 2000 at the Artificial Intelligence (AI) institute IDSIA in Lugano, Switzerland, where he stayed for six years. Since 2000, he has mainly worked on fundamental questions in AI resulting in over 200 peer-reviewed research publications and his book "Universal Artificial Intelligence" (Springer, EATCS, 2005). He has served (as PC member, chair, organizer) for numerous conferences, and reviews for major conferences and journals. He has given numerous invited lectures and his work in AI and statistics was nominated for and received several awards (UAI, IJCAI-JAIR, AGI Kurzweil, Lindley). http: //www.hutter1.net/
David Quarel is completing a PhD at the ANU. He holds a BSc in mathematics and MSc in computer science, specialising in artificial intelligence and machine learning. David has several years' experience in developing course content and distilling complex topics suitable for a wide range of academic audiences, as well as having delivered guest lectures at the ANU, and spent two years as a full-time tutor before starting his PhD.
Elliot Catt is a Research Scientist at DeepMind London and has previously completed a PhD in Universal Artificial Intelligence. He holds a BSc and MSc in mathematics and a PhD in computer science. Elliot has lectured on the topic of Advanced Artificial Intelligence at the ANU and published several pieces of work on the topic of Universal Artificial Intelligence. https: //catt.id/
作者簡介(中文翻譯)
Marcus Hutter是DeepMind倫敦分部的高級研究員，也是澳大利亞國立大學（ANU）研究學院計算機科學系（RSCS）的教授（全職至2019年，之後榮譽教授）。他是持續進行中的人類知識壓縮競賽的主席。他於1992年獲得慕尼黑工業大學計算機科學碩士學位，1996年獲得理論粒子物理學博士學位，並於2003年完成博士後研究資格。在開始學術生涯之前，他在多家公司擔任軟體開發人員多年。他於2000年加入瑞士盧加諾的人工智慧研究所IDSIA，並在那裡待了六年。自2000年以來，他主要從事人工智慧的基礎問題研究，發表了200多篇同行評審的研究論文，並出版了他的著作《通用人工智慧》（Springer，EATCS，2005）。他曾擔任多個會議的PC成員、主席和組織者，並為主要會議和期刊審稿。他曾發表多次邀請演講，並在人工智慧和統計學方面的工作被提名並獲得多個獎項（UAI，IJCAI-JAIR，AGI Kurzweil，Lindley）。http://www.hutter1.net/
David Quarel正在澳大利亞國立大學攻讀博士學位。他擁有數學學士學位和計算機科學碩士學位，專攻人工智慧和機器學習。David在開發課程內容和簡化複雜主題以適應廣泛的學術觀眾方面有數年的經驗，並在澳大利亞國立大學擔任客座講師，並在攻讀博士學位之前擔任全職導師兩年。
Elliot Catt是DeepMind倫敦分部的研究科學家，之前完成了通用人工智慧的博士學位。他擁有數學學士學位和碩士學位，以及計算機科學博士學位。Elliot曾在澳大利亞國立大學講授高級人工智慧課程，並在通用人工智慧主題上發表了多篇作品。https://catt.id/
