How Do You Calculate the Probability of a Rat Being in Room 4 After Two Moves?

In summary, the rat can access room 2 from 3 only if he is in room 1, and the probability he will be in room 4 after his second move is calculated by multiplying A2 by the column matrix [1 0 0 0].
  • #1
JeffNYC
26
0
I've attached the diagram of 4 rooms, which a rat must move through. Each period he changes his room (his state). As you can see if you click on the image, the rat cannot access room 2 from 3, vice versa.

If I assume the rat begins in room 1, how do I calculate the probability he will be in room 4 after his second move? I have the transitional probability matrix correct, I'm just not sure how to move forward.

rat markov chain.GIF


Thank you,

Jeff
 
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  • #2
Set up the "transition matrix". According to your picture, if the rat is in room 1, the is a 1/3 chance he will move to each of 2, 3, 4. That means you want your first column to be [0 1/3 1/3 1/3]. That's because you will be multiplying the matrix by a column matrix with entries representing the probability the rat is in room 1, 2, 3, or 4 respectively. If you know for certain the rat is in room 1, then your column matrix is [1 0 0 0] and it is the first column of the matrix that multiplies that first 1.

Similarly, if the rat is in room 2 the probability is 1/2 that it will move to room 1 and 1/2 that it will move to room 4: the second column in your matrix must be [1/2 0 0 1/2].

If the rat is in room 3 the probability is also 1/2 that it will move to room 1 and 1/2 that it will move to room 4 so your third column is the same as the second column.

Finally, if the rat is in room 3, the probability is 1/3 that it will move to room 1, 1/3 that it will move to room 2, and 1/3 that it will move to room 3 so the fourth column is [1/3 1/3 1/3 0].

Your transition matrix is
[tex]A= \left[\begin{array}{cccc} 0 & \frac{1}{3} & \frac{1}{3} & \frac{1}{3} \\ \frac{1}{2} & 0 & 0 \frac{1}{2} \\ \frac{1}{2} & 0 & 0 \frac{1}{2} \\ \frac{1}{3} & \frac{1}{3} & \frac{1}{3} & 0\end{array}\right][/tex]

Is that what you have?

To find "the probability he will be in room 4 after his second move If the rat begins in room 1" you need to calculate A2 times the column matrix [1 0 0 0].
 
  • #3
Thanks - that's what I thought, but I wasn't sure about the treatment of the initial probability vector.

Jeff
 

Related to How Do You Calculate the Probability of a Rat Being in Room 4 After Two Moves?

1. What is a Markov Chain?

A Markov Chain is a mathematical model used to describe a sequence of events in which the probability of each event depends only on the state of the previous event. It is used to model situations where the future state of a system depends only on the current state and not on the previous states.

2. How does a Markov Chain relate to a rat in 4 rooms?

In the context of a rat in 4 rooms, a Markov Chain can be used to model the movement of the rat between the different rooms. The probability of the rat moving to a certain room depends on its current location and not on its previous movements.

3. What are the applications of Markov Chains?

Markov Chains have various applications in different fields such as finance, genetics, and natural language processing. They are commonly used to model and analyze systems that involve random patterns and transitions, such as stock market movements, genetic sequences, and speech recognition.

4. How are transition probabilities calculated in a Markov Chain?

Transition probabilities in a Markov Chain are calculated by observing the system and collecting data on the probabilities of each event occurring. These probabilities can then be used to create a transition matrix, which represents the probabilities of transitioning from one state to another.

5. What are the limitations of Markov Chains?

One limitation of Markov Chains is that they assume that the future state of a system depends only on the current state, which may not always be true in real-world situations. Additionally, Markov Chains can become complex and difficult to analyze when the number of states and transitions in a system increases.

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