摘要翻译：
本世纪的第一个十年见证了通用人工智能的第一个数学理论的萌芽。这一通用人工智能(UAI)理论对许多理论、哲学和实践人工智能问题做出了重大贡献。在以book（Hutter,2005）为高潮的一系列论文中，为超级智能agent(AIXI)建立了一个激动人心的健全和完整的数学模型，并对其进行了严格的分析。尽管目前大多数人工智能研究人员回避讨论智能，但获奖的博士论文(Legg，2008)提供了哲学嵌入，并研究了基于UAI的理性智能的普遍度量，该度量是正式的、客观的和非人类中心的。最近，JAIR的论文（Veness et al.2011)导出了AIXI的有效近似并进行了实验研究。这一实际突破产生了一些令人印象深刻的应用，最终平息了早先关于UAI只是一种理论的批评。第一次，在不提供任何领域知识的情况下，同一个agent能够自适应地适应不同范围的交互环境。例如，AIXI能够通过试错从零开始学习玩TicTacToe、Pacman、Kuhn扑克和其他游戏，甚至不提供游戏规则。这些成果给了新的希望，即人工通用智能的宏伟目标并非难以捉摸。本文在上下文中提供了UAI的非正式概述。它试图温和地介绍一个非常理论，形式和数学的主题，并讨论哲学和技术成分，智力的特点，一些社会问题，以及UAI的过去和未来。
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英文标题：
《One Decade of Universal Artificial Intelligence》
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作者：
Marcus Hutter
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最新提交年份：
2012
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning PhD thesis (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, without providing any domain knowledge, the same agent is able to self-adapt to a diverse range of interactive environments. For instance, AIXI is able to learn from scratch to play TicTacToe, Pacman, Kuhn Poker, and other games by trial and error, without even providing the rules of the games.   These achievements give new hope that the grand goal of Artificial General Intelligence is not elusive.   This article provides an informal overview of UAI in context. It attempts to gently introduce a very theoretical, formal, and mathematical subject, and discusses philosophical and technical ingredients, traits of intelligence, some social questions, and the past and future of UAI.
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PDF链接：
https://arxiv.org/pdf/1202.6153