I'm trying to mathematically formalize the "green eyed logic puzzle" problem described in this video: https://www.youtube.com/watch?v=98TQv5IAtY8

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I'm trying to mathematically formalize the "green eyed logic puzzle" problem described in this video: https://www.youtube.com/watch?v=98TQv5IAtY8

Mathematics
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Let me rephrase the problem in a different way that is somewhat equivalent: 1) There are 100 robots. 2) Every robot knows everything that can be logically deduced from what they currently know. 3) Every robot knows the color of every other robot. 4) Every robot knows whether or not another robot has shut down. 5) If a robot knows its own color to be red, it will shut down at the first second of the next minute. 6) Every robot knows the facts listed above. 7) Every robot is red. We introduce the following fact: 8) Every robot receives a message, which they know has been sent to all other robots, which states that at least one robot is red. The question of the problem is then: What happens to the robots? The answer presented by the video is that all robots shut down after 100 minutes. I've been thinking about how to formalize the problem.
I'm going to start by simply only considering the colors of the robots, and only considering \(4\) robots. We'll give each robot a number from \(1\) to \(n\). We'll represent a robot's knowledge base as a tuple of sets. The \(i\)th element in the tuple will be the possible states a robot thinks the \(i\)th robot can be in. So for the \(1\)st robot, we will represent it's knowledge base as follows\[ (\{n,r\}, \{r\}, \{r\}, \{r\}) \]Another way we could represent this knowledge base is as follows\[ \{(n,r,r,r) ,(r,r,r,r)\} \]
Now I'm going to introduce a new concept, a means of combining two knowledge bases. We can think of it as this: What robot \(1\) can deduce robot \(2\)'s knowledge base to be. First, consider robot \(2\)'s knowledge base: \[ (\{r\}, \{n,r\}, \{r\},\{r\}) \]However, when robot \(1\) is deducing what robot \(2\) can know, it must add its own ignorance into \(2\)'s ignorance. Even thought robot \(1\) knows robot \(2\) knows robot \(1\)'s color, it has to consider both possibilities. The result is as follows: \[ (\{n,r\}, \{n,r\}, \{r\}, \{r\}) \]Another way to represent this is: \[ \{(n,n,r,r), (n,r,r,r), (r,n,r,r), (r,r,r,r)\} \]

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Finally we can consider what robot \(1\) must deduces that \(2\) must deduce that \(3\) must deduce that \(4\) must deduce, and the result is: \[ (\{n,r\},\{n,r\},\{n,r\},\{n,r\}) \]And another way to represent this is as: \[ \{n,r\}\times\{n,r\}\times\{n,r\}\times\{n,r\} \]Where \(\times\) is the Cartesian product.
I will call this the "global knowledge". This represents the list of all states a robot can deduce the other robots could think to be possible. Remember that when your knowledge set is large, that means there is more uncertainty and so you are actually more ignorant. The omniscience robot would have a knowledge set of one state (the truth), while the completely ignorant robot would have a knowledge set of all states (every possibility). Knowledge lets you eliminate states. The set \(\{n, r\}^4\) also incidentally the set of all possible states, meaning that the global knowledge is completely ignorant.
The local knowledge for any robot is its own knowledge set. A statement is said to introduce no information if it doesn't modify any robot's local knowledge. However, though the message sent out all robots did not modify any local knowledge, it modified the global knowledge. It made the global knowledge out to be: \[\{n,r\}^4 \setminus \{(n,n,n,n)\}\]
Even \(2^4 = 16\) is a lot to write out, let's just start with a case of \(2\) robots... The knowledge set of robot \(1\): \[ \{(n, r),(r,r)\} \]The knowledge set of robot \(2\): \[ \{(r, n),(r,r)\} \]The knowledge set of the messages sent out to the robots: \[ \{(n, r), (r, n), (r,r)\} = \{n,r\} \times \{n,r\} \setminus \{(n,n)\} \]That is, since at least one robot is red, the state \((n,n)\) can be ruled out. All robots intersect this with there own knowledge set and see no change, so technically none of them learned anything new from it. However, let's consider what robot \(1\) could consider robot \(2\) to know before the message: \[ \{(n,n), (n,r), (r,n), (r,r)\} = \{n,r\}\times \{n,r\} \]To be clear, robot \(1\) knows that that robot \(2\) knows robot \(1\)'s color to be red or not red... but it doesn't know what \(2\) knows. Hence this is what robot \(1\) can deduce what robot \(2\) might know. The message doesn't modify robot \(1\)'s own knowledge set, but it does modify this knowledge set to be \[ \{(n, r), (r, n), (r,r)\} \]Since robot \(1\) knows this message was sent to robot \(2\) as well.
i'm sorry to come to someone else's tag here and ask for help but this is an emergency! and I need help ASAP! i'd really appreciate it if one of u helped!
Hello?? Anyone here?
Now let's go to the \(n=3\) case. Here is the global knowledge set. I'm partitioning it based on whether robot \(1\) is red or not\[ \{(n,n,r), (n,r,n), (n,r,r)\} \cup\{ (r,n,n),(r,n,r), (r,r,n), (r,r,r)\} = A\cup B \]The \(A\) case is very familiar. It is like the \(n=2\) case is happening for robots \(2\) and \(3\).
Guys, I'm open to suggestions, questions, etc.
I'm not completely sure what I'm doing here.
I see set theory being used.. like A or B so the set of a is umm the chances of the robot being not red or red and the set of B is a bigger chance of the robot being red.
Yes
\((r,n,n)\) means robot 1 is red, robot 2 is not red, robot 3 is not red.
Robot 1 can deduce \((r,r,r)\) and \((n,r,r)\) because it knows the other two are red.
Robot 2 can deduce \((r,n,r)\) and \((r,r,r)\) because it knows the other two are red.
Robot 1 asks the question: What can both myself and robot 2 know? It realizes that both know the third robot is red. It deduces: \((n,r,r),(n,n,r),(r,n,r), (r,r,r) \). That is, it deduces ever state where the final coordinate is \(r\).
(r,r,r) means robot 1 is red...so as robot 2 and 3
Then robot 1 asks the question, what do we all know together. Sadly, there is nothing that they all collectively know.
here's another way to go about it, as time passes they know its not just atleast one but atleast 2 amd 3 and so on
see if you can model that
for example the 3 case, once a day passes and no one has left, all 3 know now that atleast 2 of them must have green eyes
how to model that hmm
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there your green eyes is present rofl
Yeah I was thinking shutdown needs to be a part of it as well, so we need to have \(\{n,r,s\}\), where \(s\) is the shutdown state. We can also have time simple be \(n\in \mathbb N\).
I've also noticed that if I added a robot with non-red lights, it would would see 100 robots with red, while every other robot would see 99 robots with red. So by the 100th minute, it would not deduce it self to have a red light.
There is one thing about this puzzle which I've always found extremely dubious, and that is the assumption that the robots make about the other robots. They assume that other robots will use inductive reasoning, but that assumption is only say if other robots make that assumption. It's circular deduction, isn't it?
It makes sense in the n=2 case
Hmmm, I guess it does make a bit more sense. My model is getting a bit better. so an example state might be:\[ (s,s,s,s,4) \]meaning that they all shut down at minute 4
A robot only needs to consider what he thinks a red eyes robot is thinking.
So at time of message, robot 1 looks at red robot 2 and deduces his knowledge set to be: \[ (1, n/r, n/r, r,r,r ,...) \]All the red robots have to be counting the same number of red robots.
They just need to be able to deduce whether there is \(n-1\) or \(n\) red robots.
for example if it sees 2 red and 1 non red then it knows if its red then the 2 red should dissappear in 3 days, if they dissappear in 2 days then it was also non red
so every robot should have a count total number of red and non red if they see anyone dissappear on days = (number of red -1 ) then it knows it is non red and continues to function, if it sees number of red and number of red days have pased then it shuts off, all robots will follow same method
i wonder how it would work, if new robots were added at different times into the mix
It would fall apart
ya, but i wonder if there is still some way to keep track or like atleast be close, like if the new robot sees someone dissappear then it knows the the previous count of the other robots +/- 1
Adding non-red robots won't change anything, because it won't change any robot's counts and robots know non-red won't shut down
right
Adding a red robot will depend on what the red robots know and what the other robots know the red robot knows
If the robots know that the red robot got the message and knows the time, it's no different than if it was there from the beginning.
I think otherwise it would work as if the robot wasn't added

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