摘要翻译:
当Kurt Goedel在1931年为理论计算机科学奠定基础时,他还介绍了人工智能(AI)理论的基本概念。尽管后来的人工智能研究主要集中在启发式上,启发式在许多实际的人工智能应用中仍然发挥着重要作用,但在新千年里,人工智能理论终于成为一门成熟的形式科学,通过Goedel理论和概率论的结合,获得了生活在未知环境中的具身智能体的重要优化结果。在这里,我们回顾人工智能历史上的重要里程碑,提到最近的重要成果,并推测我们对未来25年的预期,强调正在进行的戏剧性硬件加速的重要性,并讨论哥德尔启发的、自我参考的、自我改进的通用问题解决器。
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英文标题:
《2006: Celebrating 75 years of AI - History and Outlook: the Next 25
Years》
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作者:
Juergen Schmidhuber
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最新提交年份:
2007
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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:
When Kurt Goedel layed the foundations of theoretical computer science in 1931, he also introduced essential concepts of the theory of Artificial Intelligence (AI). Although much of subsequent AI research has focused on heuristics, which still play a major role in many practical AI applications, in the new millennium AI theory has finally become a full-fledged formal science, with important optimality results for embodied agents living in unknown environments, obtained through a combination of theory a la Goedel and probability theory. Here we look back at important milestones of AI history, mention essential recent results, and speculate about what we may expect from the next 25 years, emphasizing the significance of the ongoing dramatic hardware speedups, and discussing Goedel-inspired, self-referential, self-improving universal problem solvers.
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PDF链接:
https://arxiv.org/pdf/0708.4311