AI 与机器学习github.com编辑精选
《人工智能编程范例》（1992）
Paradigms of Artificial Intelligence Programming (1992)
2018 — 2022，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
Peter Norvig 的经典著作《人工智能编程范式》（PAIP）的完整电子版，托管在 GitHub 上。书中以 Common Lisp 讲解经典符号 AI 技术（搜索、解释器、Prolog、专家系统等），同时也是一部高水准的编程技艺教材。多次登上 HN 首页，被广泛视为历久弥新的编程经典。
为什么经久不衰：它把编程当作一门手艺来教，AI 内容虽旧但其中的启发式算法思想至今仍有实用价值，且全书免费开放。
HN 评论精选
老式 AI 技术在今天工程实践中仍有巨大价值
五大编程书籍之一。旧式 AI 其实就是今天最前沿的计算机工程，里面有无穷的免费午餐：现代 SAT 求解器性能惊人；用 Prolog/Datalog 写复杂系统配置器如施魔法；专家系统从未像今天这样有用——凡是看到靠复杂业务逻辑和高价咨询顾问支撑的昂贵系统，都该知道有更好的办法。（我自己就用 SAT 求解器来部分初始化神经网络参数。）
MAXPOOL查看英文原文
One of the top 5 programming books. Old AI is today's bleeding edge computer engineering. There is an enourmous amount of free lunches for computer engineers and software startups in the old school artificial intelligence. * modern SAT solver performance is impressive. They can solve huge problems. * Writing a complex systems configurator with Prolog or Datalog can be like magic. * Expert systems. There has never been so much use for them than today. Whenever you see expensive systems utilizing complex mess of "business logic" and expensive consultants, you should know there is a better way. (I use SAT-solvers to partially initialize neural network parameters).
它既是编程进阶教材又是老 AI 技术概览
这本书是不过时的经典，本质上是两件事：一本用基础 Common Lisp 写的进阶编程书——如果你从未深入研读他人代码来提升自己，这是很好的起点，编程如艺术；同时概述了一些老 AI 技术、解释器和解析器，这些老技术如今都是值得了解的启发式算法。
nabla9查看英文原文
This book is timeless classic that is not getting old. It's basically two things: * Learn to program book written in very basic old school Common Lisp. Or, learn to program after you already know how to program. If you never really dwell deeply into code that others write to improve your own skills this is good book so start. It's programming as art or literature. * Overview of some old AI techniques, interpreters and parsers. Old AI techniques are today's good to know heuristic algorithms.
符号 AI 与神经网络各有长处，未来可能需要混合范式
我和 Peter 大约同期各写了一本 Lisp 书，之后在圣地亚哥的 Lisp 大会上认识他。追踪他三十年的写作，我觉得他对软件和算法有更高层次的视野。关于符号 AI 我心情复杂：我如今在一家全用 Common Lisp + 传统符号 AI 的公司工作，但我职业生涯最大的成功来自神经网络和深度学习。我觉得我们需要某种新的混合范式，但那超出我的能力。
mark_l_watson查看英文原文
I wrote a small Common Lisp book for Springer Verlag about the same time that Peter wrote this fantastic book and I then met him shortly thereafter at a Lisp Users Vendors conference in San Diego. After 30 years of following his writing, Python notebooks, etc., I think that he just has a higher level view of software and algorithms. There is some talk on this thread about good old fashioned symbolic AI. I have mixed feelings about this. I am currently working for an all-in Common Lisp + GOFAI company, but most of my best successes in my career involved neural networks, and later deep learning. I think we need a new hybrid approach but it is above my skill level to know what that would be. I keep hoping to see some new research and new paradigms.
AI 内容虽旧，但编程建议永恒
这本书能免费在线阅读太好了！它一直是我最喜爱的编程书籍之一，我自己的那本已经翻得起了毛边。它讲的不是 2018 年的前沿 AI，但其中的通用编程建议是永恒的，AI 示例可以当作一个有趣的练习领域。
eliben查看英文原文
Wow, it's great this book is now available online for free! It's definitely one of my all-time-favorite programming books - my own copy is well worn by use. It's not exactly cutting edge AI in 2018, but the general programming advice is timeless and the AI samples can be seen as a fun domain to play in.
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