Ken Stanley: Discovery Without Objectives

推荐理由

I've seen a couple of really interesting talks recently about the surprising successfulness of objective-less search by Ken Stanley

推荐mkl · 原文2018年9月

说明

这是2012年由fzambetta75发布的一部演讲，主题归在Machine learning & deep learning。它讲的是open-ended search这一支里的具体问题，而不是把整个领域扫一遍。适合已经能看懂基本术语、想继续往下走的人。内容上可以概括成：A 92-minute RMIT University seminar in which Ken Stanley argues that setting an objective can block achieving it. He presents objective-less, novelty-driven search as an alternative approach to innovation and discovery, drawing on evolutionary computation.这些读者给出的理由，核心是：Cited as a source for the idea that open-ended search can beat objective-driven optimization, though one commenter found parts of it fluffy.讲法不绑某一条新闻，过几年仍然可以当材料看。从2016年到2018年，有1位不同的读者在1个不同月份把它推荐出来，其中明确叫别人去看的有0次。适合一次性看完。讲者把一个判断讲透，演示是在给这个判断配例子。如果已经会了基本定义，就把注意力放在它怎么把open-ended search变成能跟着复述的例子。

视频信息

频道

fzambetta75

时长

1 小时 32 分

发布年份

2012

同主题更多

• The spelled-out intro to neural networks and backpropagation: building micrograd
• But what is a neural network? | Deep learning chapter 1
• AlphaGo - The Movie | Full award-winning documentary
• Transformers, the tech behind LLMs | Deep Learning Chapter 5
• USENIX Security '18-Q: Why Do Keynote Speakers Keep Suggesting That Improving Security Is Possible?
• Lecture 1 | Machine Learning (Stanford)