One possible approach to develop the best possible general learning algorithm Author: Martí Llopart Introduction In the world we live in, there are many problems that need to be urgently solved: climate change[1], the risk of a new pandemic[2], wealth inequality[3], the aging population[4] and more. All of these problems...
Author: Martí Llopart Introduction In the world we live in, there are many problems that need to be urgently solved: climate change[1], the risk of a new pandemic[2], wealth inequality[3], the aging population[4] and more. All of these problems are hugely complex and solving them requires vast amounts of intelligence....
One possible approach to develop the best possible general learning algorithm
Author: Martí Llopart
Introduction
In the world we live in, there are many problems that need to be urgently solved: climate change[1], the risk of a new pandemic[2], wealth inequality[3], the aging population[4] and more. All of these problems are hugely complex and solving them requires vast amounts of intelligence. In order to address that, there’s a tool that comes in very handy: Artificial Intelligence. We are all familiar with AI, but to put it shortly, it’s the intelligence demonstrated by machines[5]. In recent years, AI has proven to be a game changer for industries such as healthcare and finance, but most experts agree... (read 2020 more words →)
Author: Martí Llopart
Introduction
In the world we live in, there are many problems that need to be urgently solved: climate change[1], the risk of a new pandemic[2], wealth inequality[3], the aging population[4] and more. All of these problems are hugely complex and solving them requires vast amounts of intelligence. In order to address that, there’s a tool that comes in very handy: Artificial Intelligence. We are all familiar with AI, but to put it shortly, it’s the intelligence demonstrated by machines[5]. In recent years, AI has proven to be a game changer for industries such as healthcare and finance, but most experts agree that we are just at the beginning of what has... (read 3613 more words →)
Hey! Thanks for your comment.
This algorithm won't get caught in a loop like the one you mentioned, because it uses the same process as the one described in the AutoML-Zero paper. In the article, they 'found a better algorithm and iterated' without any problem whatsoever, using the processes described in figures 1 and 2. Please check the paper for that.
About your second point: that's exactly the aim of the experiment, to know if a strictly-better agent can be found with an automatic process. If we don't get there using substantial computation within an acceptable amount of time, then the experiment will have failed. But, as with all experiments, there's good reasons try.
Third:... (read more)