Dear Fellow Scholars, this is Two Minute Papers with Károly Zsolnai-Fehér.
You know that I am always excited to tell you about news where AI players manage to
beat humans at more and more complex games.
Today we are going to talk about DOTA 2 which is a multiplayer online battle arena game
with a huge cult following and world championship events with a prize pool of over 40 million
dollars.
This is not just some game, and just to demonstrate how competitive it is and how quickly it is
growing, last time we talked about this in Two Minute Papers episode 180 where an AI
beat some of the best players of the game in a limited 1 versus 1 setting, and the prize
pool was 20 million dollars back then.
This was a huge milestone as this game requires long-term strategic planning, has incomplete
information and a high-dimensional continuous action space, which is a classical nightmare
situation for any AI.
Then, the next milestone was set to defeat a human team in the full 5 versus 5 game,
and I promised to report back when there is something new on this project.
So here we go.
If you look through the forums and our YouTube comments, it is generally believed that this
is so complex that it would never ever happen.
I would agree that the search space is indeed stupendously large and the problem is notoriously
difficult, but whoever thinks this will never be solved has clearly not been watching enough
Two Minute Papers.
Now, you better hold on to your papers right away, because this video dropped 10 months
ago, in August 2017, and since then, the AI has played 180 years worth of gameplay against
itself every single day.
80% of these games it played against itself, and 20% against its past self, and even though
five of these bots are supposed to work together as a team, there is no explicit communication
channel between them.
And now, it is ready to play 5 versus 5 matches.
Some limitations still apply, but since then, the AI was able get a firm understanding of
the importance of teamfighting, predicting the outcome of future actions and encounters,
ganking, or in other words, ambushing unsuspecting opponents and many other important pieces
of the game.
The May 15th version of the AI was evenly matched against OpenAI's in-house team, which
is a formidable result, and I find it really amusing that these scientists were beaten
by their own algorithm.
This is, however, not a world class DOTA 2 team.
And the crazy part is that the next version of the AI was tested three weeks later, and
it not only beat the in-house team easily, but also defeated several other teams and
a semi-professional team as well.
As it is often incorrectly said on several forums that these algorithms defeat humans
because they can click faster, so I will note that that these bots perform about 150-170
actions per minute, which is approximately in line with an intermediate human player,
and it is also to be noted that DOTA2 is not that sensitive to this metric.
More clicking does really not mean more winning here at all.
The human players were also able to train with an earlier version of this AI.
There will be an upcoming event on July 28th where these bots will challenge a team of
top players, so stay tuned for some more updates on this!
There is no paper yet, but I've put a link to a blog post and the full video in the description,
and it is a gold mine of information and was such a joy to read through.
So, what do you think?
Who will win?
And is a 5 versus 5 game in DOTA 2 more complex than playing Starcraft 2?
If you wish to hear more about this, please consider helping us tell this story to more
people and convert them into Fellow Scholars by supporting the series through Patreon,
and as always, we also accept Bitcoin, Ethereum, and Litecoin, the addresses are in the video
description.
And if you are now in the mood to learn some more about DOTA 2, I recommend taking a look
at Day9's channel, I've put a link to a relevant series in the video description.
Highly recommended.
So there you go, a fresh Two Minute Papers episode, that's not two minutes and it's not
about a paper.
Yet.
Love it.
Thanks for watching and for your generous support, and I'll see you next time!