<p>While I don't know any digital equivalent of that particular game or neither I was introduced to RL this way either. But, still there are other games and videos that might help you to teach your students RL. Some of them were actually very useful when I was a beginner.</p>
<ol>
<li>EVOLUTION (By Keiwan Donyagard)</li>
</ol>
<p><a href="https://i.sstatic.net/SbRko.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/SbRko.png" alt="EVOLUTION APP (It's a game to make people familiar with Reinforcement Learning)" /></a></p>
<p>It's a downloadable Android App based Game where the players create creatures with bones (represented with Black Stick), joints (represented with Red circle/spot) and Muscles (red , connecting the bones). The organisms starts hundreds of thread and learns to walk bit by bit and after each iteration by iteration, they become perfect learners after few minutes.</p>
<p>Link : <a href="https://play.google.com/store/apps/details?id=com.keiwando.Evolution&amp;hl=en_US&amp;gl=US" rel="nofollow noreferrer">https://play.google.com/store/apps/details?id=com.keiwando.Evolution&amp;hl=en_US&amp;gl=US</a></p>
<ol start="2">
<li><p>Flappy Bird Video (Uses a bit of Deep Learning Methods, an example of Deep RL)
<a href="https://i.sstatic.net/GHXmk.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/GHXmk.jpg" alt="AI Playing Flappy Bird" /></a>
<a href="https://www.youtube.com/watch?v=WSW-5m8lRMs" rel="nofollow noreferrer">https://www.youtube.com/watch?v=WSW-5m8lRMs</a></p>
</li>
<li><p>Google's DeepMind Playing Atari
<a href="https://i.sstatic.net/7DvB2.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/7DvB2.jpg" alt="Google DeepMind playing Atari" /></a>
<a href="https://www.youtube.com/watch?v=V1eYniJ0Rnk" rel="nofollow noreferrer">https://www.youtube.com/watch?v=V1eYniJ0Rnk</a></p>
</li>
</ol>
<p>There are some experiments where AI did outsmart their creators and performed unexpectedly well too.</p>
<p>Here are some videos:</p>
<ol>
<li><p><a href="https://www.youtube.com/watch?v=GdTBqBnqhaQ" rel="nofollow noreferrer">https://www.youtube.com/watch?v=GdTBqBnqhaQ</a> (By Two Minute Papers)
<a href="https://i.sstatic.net/s2oV7.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/s2oV7.jpg" alt="Two Minute Papers' video" /></a></p>
</li>
<li><p>OpenAI Hide and Seek which actually breaks the game (<a href="https://www.youtube.com/watch?v=kopoLzvh5jY" rel="nofollow noreferrer">https://www.youtube.com/watch?v=kopoLzvh5jY</a>)</p>
</li>
</ol>
<p><a href="https://i.sstatic.net/rIOwE.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/rIOwE.jpg" alt="OpenAI Hide and Seek" /></a></p>
<p><em>Motivation: Reinforcement Learning and Deep Reinforcement Learning is an important field of study in AI because it is a general way to Build an AGI and ASI. (AGIs called Artificial General Intelligence and ASIs are called Artificial Super Intelligence.) The core development and framework of such systems have already been put in form of AIXI and AIXI-tl and they would definitely change the way whole humanity looks at it. Some of the notable researchers claim that Artificial Super Intelligence would be the last ever the biggest invention of Humanity and the most terrifying thing is that we still don't have a proper framework and ethical standards set for use of such super intelligent systems (Superintelligence: Paths, Dangers, Strategies, Nick Bostrom.). While some theoretical paper do have measures of frameworks on dangers of such systems (<a href="https://arxiv.org/abs/1607.00913" rel="nofollow noreferrer">https://arxiv.org/abs/1607.00913</a>), but we still are far from specific idea about the matter. This is primarily because of lack of researchers here in this particular field. We hope more and more people join and contribute to the emergence, control and setup of ethical standards of such super intelligent Systems.</em></p>

CC BY-SA 4.0
2021-02-12T04:35:05.173Z
2021-02-12T04:35:05.173Z
Abhas Kumar Sinha
<p>I came accross this handout of <a href="https://www.aiunplugged.org/english.pdf" rel="nofollow noreferrer">aiunplugged</a>, specifically the topic of reinforcment learning (on page 12). I planned to do this boardgame, where students experience the concept of reinforcement learning. They play a simplefied (3x3 field) version of chess only with pawns. The goal of each player is to either reach one pawn to the side of the opponent, by capturing all of the figures (of the opponent) or blocking the opponent (no moves possoble for the opponent). One player is the machine and one is the human. The machine player has an additional sheet with possible moves based on the game state, which he/she first randomly chooses from. In the beginning the machine is losing a lot, however over time, when it starts to win, it will keep this move. Over time, when the bad moves of the machine are getting eliminated, the machine gets better, and after a while impossible to beat.</p>
<p>So now my question: <strong>Since teaching from home is still ongoing, is there any digital equivalent of this game or does anyone know anything similar, where students should experience machine learning in a simplified manner?</strong></p>
<p>Thank you</p>

CC BY-SA 4.0
2021-02-12T08:10:59.783Z
Matt Parker et al made a [video](https://www.youtube.com/watch?v=R9c-_neaxeU) of a team doing this (tik tak too / noughts and crosses) at the museum of industry in Manchester.
ctrl-alt-delor
CC BY-SA 4.0
2021-02-12T17:59:27.230Z
@ctrl-alt-delor this is a nice alternative to this game.
thehayro
<artificial-intelligence><machine-learning>
Trying out the concepts of machine learning during teaching from home
# Trying out the concepts of machine learning during teaching from home

(Asked by: username_0 on 2021-02-11)

I came accross this handout of [aiunplugged](https://www.aiunplugged.org/english.pdf), specifically the topic of reinforcment learning (on page 12). I planned to do this boardgame, where students experience the concept of reinforcement learning. They play a simplefied (3x3 field) version of chess only with pawns. The goal of each player is to either reach one pawn to the side of the opponent, by capturing all of the figures (of the opponent) or blocking the opponent (no moves possoble for the opponent). One player is the machine and one is the human. The machine player has an additional sheet with possible moves based on the game state, which he/she first randomly chooses from. In the beginning the machine is losing a lot, however over time, when it starts to win, it will keep this move. Over time, when the bad moves of the machine are getting eliminated, the machine gets better, and after a while impossible to beat.

So now my question: **Since teaching from home is still ongoing, is there any digital equivalent of this game or does anyone know anything similar, where students should experience machine learning in a simplified manner?**

Thank you

**Tags:** artificial-intelligence, machine-learning

> **Comments:**
> **username_1**: Matt Parker et al made a [video](https://www.youtube.com/watch?v=R9c-_neaxeU) of a team doing this (tik tak too / noughts and crosses) at the museum of industry in Manchester.  
> **username_0**: @username_1 this is a nice alternative to this game.  

---

## 1 answers

### Answer by username_2 on 2021-02-12. Score: 3

While I don't know any digital equivalent of that particular game or neither I was introduced to RL this way either. But, still there are other games and videos that might help you to teach your students RL. Some of them were actually very useful when I was a beginner.

1. EVOLUTION (By Keiwan Donyagard)

[![EVOLUTION APP (It's a game to make people familiar with Reinforcement Learning)](https://i.sstatic.net/SbRko.png)](https://i.sstatic.net/SbRko.png)

It's a downloadable Android App based Game where the players create creatures with bones (represented with Black Stick), joints (represented with Red circle/spot) and Muscles (red , connecting the bones). The organisms starts hundreds of thread and learns to walk bit by bit and after each iteration by iteration, they become perfect learners after few minutes.

Link : [https://play.google.com/store/apps/details?id=com.keiwando.Evolution&hl=en\_US≷=US](https://play.google.com/store/apps/details?id=com.keiwando.Evolution&hl=en_US&gl=US)

2. Flappy Bird Video (Uses a bit of Deep Learning Methods, an example of Deep RL)
   [![AI Playing Flappy Bird](https://i.sstatic.net/GHXmk.jpg)](https://i.sstatic.net/GHXmk.jpg)
   <https://www.youtube.com/watch?v=WSW-5m8lRMs>
3. Google's DeepMind Playing Atari
   [![Google DeepMind playing Atari](https://i.sstatic.net/7DvB2.jpg)](https://i.sstatic.net/7DvB2.jpg)
   <https://www.youtube.com/watch?v=V1eYniJ0Rnk>

There are some experiments where AI did outsmart their creators and performed unexpectedly well too.

Here are some videos:

1. <https://www.youtube.com/watch?v=GdTBqBnqhaQ> (By Two Minute Papers)
   [![Two Minute Papers' video](https://i.sstatic.net/s2oV7.jpg)](https://i.sstatic.net/s2oV7.jpg)
2. OpenAI Hide and Seek which actually breaks the game (<https://www.youtube.com/watch?v=kopoLzvh5jY>)

[![OpenAI Hide and Seek](https://i.sstatic.net/rIOwE.jpg)](https://i.sstatic.net/rIOwE.jpg)

*Motivation: Reinforcement Learning and Deep Reinforcement Learning is an important field of study in AI because it is a general way to Build an AGI and ASI. (AGIs called Artificial General Intelligence and ASIs are called Artificial Super Intelligence.) The core development and framework of such systems have already been put in form of AIXI and AIXI-tl and they would definitely change the way whole humanity looks at it. Some of the notable researchers claim that Artificial Super Intelligence would be the last ever the biggest invention of Humanity and the most terrifying thing is that we still don't have a proper framework and ethical standards set for use of such super intelligent systems (Superintelligence: Paths, Dangers, Strategies, Nick Bostrom.). While some theoretical paper do have measures of frameworks on dangers of such systems (<https://arxiv.org/abs/1607.00913>), but we still are far from specific idea about the matter. This is primarily because of lack of researchers here in this particular field. We hope more and more people join and contribute to the emergence, control and setup of ethical standards of such super intelligent Systems.*


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