Answers.Body: <p><a href="https://bair.berkeley.edu/blog/2017/07/18/learning-to-learn/" rel="nofollow noreferrer"><em>Learning to learn</em></a> (also known as <a href="https://arxiv.org/pdf/1606.04474.pdf" rel="nofollow noreferrer"><em>meta-learning</em></a>) is <strong>very important</strong> for the development of artificial general intelligence (AGI), given that one of the desirable and fundamental properties of an AGI is the <em>adaptability</em> to different environments and the ability to <a href="https://arxiv.org/abs/1802.07569" rel="nofollow noreferrer">continually learn</a>, and meta-learning can be used to achieve that.</p>
  
  <p>Meta-learning is thus related to multi-task, <a href="https://arxiv.org/abs/1802.07569" rel="nofollow noreferrer">continual (or lifelong)</a> and <a href="https://www.cse.ust.hk/~qyang/Docs/2009/tkde_transfer_learning.pdf" rel="nofollow noreferrer">transfer</a> learning. There are several approaches to meta-learning, such as <a href="https://arxiv.org/abs/1703.03400" rel="nofollow noreferrer">MAML</a>, but there is usually a meta-learner and a learner.</p>
  
  <p>In the paper <a href="https://arxiv.org/pdf/1604.00289.pdf" rel="nofollow noreferrer">Building Machines That Learn and Think Like People</a> (2016), Marcin Andrychowicz et al. argue that truly human-like learning and thinking
  machines (or AGI) should </p>
  
  <ol>
  <li><p>build causal models of the world that support explanation and understanding</p></li>
  <li><p>ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned</p></li>
  <li><p>harness compositionality and <strong>learning-to-learn</strong> to rapidly acquire and generalize knowledge to new tasks and situations</p></li>
  </ol>
  
  <p>Another person that thinks that meta-learning is important for the development of AGI is Ben Goertzel. See e.g. his article <a href="https://singularityhub.com/2018/07/22/from-here-to-human-level-artificial-general-intelligence-in-four-not-all-that-simple-steps/" rel="nofollow noreferrer">From Here to Human-Level Artificial General Intelligence in Four (Not All That) Simple Steps</a>. </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-11-27T19:05:08.913Z
Answers.LastActivityDate: 2020-04-13T22:10:31.230Z
Answers.LastEditDate: 2020-04-13T22:10:31.230Z
Answers.UserDisplayName: nbro
Body: <p>Some people say that abstract thinking, <a href="http://artificial-intuition.com/" rel="nofollow noreferrer">intuition</a>, common sense, and understanding cause and effect are important to make AGI.</p>
  
  <p>How important is <em>learning to learn</em> for the development of AGI?</p>
  
Tags: <philosophy><agi><meta-learning>
Title: How important is learning to learn for the development of AGI?
UserDisplayName: loopy_fun
ThreadText: # How important is learning to learn for the development of AGI?
  
  (Asked by: username_0 on 2019-11-27)
  
  Some people say that abstract thinking, [intuition](http://artificial-intuition.com/), common sense, and understanding cause and effect are important to make AGI.
  
  How important is *learning to learn* for the development of AGI?
  
  **Tags:** philosophy, agi, meta-learning
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-11-27. Score: 3
  
  [*Learning to learn*](https://bair.berkeley.edu/blog/2017/07/18/learning-to-learn/) (also known as [*meta-learning*](https://arxiv.org/pdf/1606.04474.pdf)) is **very important** for the development of artificial general intelligence (AGI), given that one of the desirable and fundamental properties of an AGI is the *adaptability* to different environments and the ability to [continually learn](https://arxiv.org/abs/1802.07569), and meta-learning can be used to achieve that.
  
  Meta-learning is thus related to multi-task, [continual (or lifelong)](https://arxiv.org/abs/1802.07569) and [transfer](https://www.cse.ust.hk/~qyang/Docs/2009/tkde_transfer_learning.pdf) learning. There are several approaches to meta-learning, such as [MAML](https://arxiv.org/abs/1703.03400), but there is usually a meta-learner and a learner.
  
  In the paper [Building Machines That Learn and Think Like People](https://arxiv.org/pdf/1604.00289.pdf) (2016), Marcin Andrychowicz et al. argue that truly human-like learning and thinking
  machines (or AGI) should
  
  1. build causal models of the world that support explanation and understanding
  2. ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned
  3. harness compositionality and **learning-to-learn** to rapidly acquire and generalize knowledge to new tasks and situations
  
  Another person that thinks that meta-learning is important for the development of AGI is Ben Goertzel. See e.g. his article [From Here to Human-Level Artificial General Intelligence in Four (Not All That) Simple Steps](https://singularityhub.com/2018/07/22/from-here-to-human-level-artificial-general-intelligence-in-four-not-all-that-simple-steps/).
  
  
  ---
  
  