Probability, knight on a 5x5 chess board, expected return time.

In summary, the conversation discusses a problem with a knight on a 5x5 chess board, where each position is numbered based on the number of steps it takes to return to the center. This problem is then turned into a random walk Markov chain with a transition matrix. The question is the expected return time starting from the center, and the solution involves solving a set of equations. The output of the equations is given, and the final question is about the expected return time if there was a probability of hitting all other states from the center.
  • #1
Gregg
459
0

Homework Statement



I have a knight on a chess board that is 5x5. I have numbered each position on the board by the amount of steps it takes from that position to get back to the centre.

It looks roughly like this

##\begin{array}{ccccc}
4 & 1 & 2 & 1 & 4 \\
1 & 2 & 3 & 2 & 1 \\
2 & 3 & 0 & 3 & 2 \\
1 & 2 & 3 & 2 & 1 \\
4 & 1 & 2 & 1 & 4
\end{array}##I have made this into a random walk Markov chain with transition matrix.

## \left(
\begin{array}{ccccc}
0 & 1 & 0 & 0 & 0 \\
\frac{1}{3} & 0 & \frac{2}{3} & 0 & 0 \\
0 & \frac{1}{2} & 0 & \frac{1}{2} & 0 \\
0 & 0 & \frac{2}{3} & 0 & \frac{1}{3} \\
0 & 0 & 0 & 1 & 0
\end{array}
\right)##The question is the expected return time starting from the centre.

I have solved the set of equations

## k_i^{\{A\}} = 0, \text{ if } i\in A ##
## k_i^{\{A\}} = 1+\sum_j p_{ij} k_j^{\{A\}}, \text{ if } i\in A^C ##I get

##k_0^{\{0\}} = 0##
##k_1^{\{0\}} = 11##
##k_2^{\{0\}} = 15##
##k_3^{\{0\}} = 17##
##k_4^{\{0\}} = 18##What do I do with these?

Edit: my guess is: Since ##P_{01} = 1 ## the answer is ##11+1=12##

If this is the case, say if there was some probability of hitting all of the other states from 0, would the expected return time be ##k^{\{0\}} = 1 + \sum_{j} p_{ij} k_j^{\{0\}} ## ?
 
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  • #2
Homework Equations ## k_i^{\{A\}} = 0, \text{ if } i\in A #### k_i^{\{A\}} = 1+\sum_j p_{ij} k_j^{\{A\}}, \text{ if } i\in A^C ##The Attempt at a Solution My guess is: Since ##P_{01} = 1 ## the answer is ##11+1=12##If this is the case, say if there was some probability of hitting all of the other states from 0, would the expected return time be ##k^{\{0\}} = 1 + \sum_{j} p_{ij} k_j^{\{0\}} ## ?
 

Related to Probability, knight on a 5x5 chess board, expected return time.

1. What is probability and how does it relate to a knight on a 5x5 chess board?

Probability is the measure of the likelihood of an event occurring. In the context of a knight on a 5x5 chess board, probability is used to determine the likelihood of the knight landing on a specific square after a certain number of moves.

2. How can the expected return time of a knight on a 5x5 chess board be calculated?

The expected return time of a knight on a 5x5 chess board can be calculated by using probability and the number of possible moves for each square on the board. This calculation involves finding the average number of moves it takes for the knight to return to its starting position after multiple iterations.

3. Why is the expected return time of a knight on a 5x5 chess board important?

The expected return time of a knight on a 5x5 chess board is important because it provides insight into the efficiency and effectiveness of the knight's movements on the board. It can also be used to optimize strategies for the knight's movements.

4. Is there a formula for calculating the expected return time of a knight on a 5x5 chess board?

Yes, there is a formula for calculating the expected return time of a knight on a 5x5 chess board. It involves using the number of possible moves for each square on the board and taking the average of these values over multiple iterations.

5. How can the expected return time of a knight on a 5x5 chess board be applied in real-world scenarios?

The expected return time of a knight on a 5x5 chess board can be applied in various real-world scenarios, such as optimizing transportation routes or predicting the efficiency of algorithms in computer science. It can also be used in game theory to analyze the movements of players in strategic games.

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