How can we solve the Infinite Monkey problem using gambling monkeys?

  • Thread starter Thread starter Firepanda
  • Start date Start date
  • Tags Tags
    Infinite
Click For Summary
SUMMARY

The Infinite Monkey problem can be effectively analyzed using discrete-time renewal processes, as outlined in Feller's "Introduction to Probability Theory and Its Applications." The expected time for a renewal to occur, specifically for the string "abracadabra," is derived from the equation (1/26)^{11} = (1/\mu)[1 + (1/26)^7 + (1/26)^{10}], where μ represents the mean time between renewals. An alternative approach involves utilizing Markov chains to compute mean first-passage times, though the renewal method is simpler and more intuitive for this problem. For further insights, readers are encouraged to explore Feller's work or modern texts on Renewal Theory.

PREREQUISITES
  • Understanding of discrete-time renewal processes
  • Familiarity with probability theory concepts
  • Knowledge of Markov chains and their applications
  • Access to Feller's "Introduction to Probability Theory and Its Applications"
NEXT STEPS
  • Study Renewal Theory in depth through Feller's texts or modern literature
  • Learn about Markov chain representations and mean first-passage time calculations
  • Explore the concept of aperiodicity in stochastic processes
  • Investigate the gambling monkeys approach as a creative solution to the Infinite Monkey problem
USEFUL FOR

Mathematicians, statisticians, and computer scientists interested in probability theory, stochastic processes, and creative problem-solving techniques related to the Infinite Monkey problem.

Firepanda
Messages
425
Reaction score
0
6789rl.png


I would have thought this would just be 2611 (in whatever units) for the expected time taken, does anyone know where the other two terms come from?

Should my expectation be drawn from some kind of distribution?

Thanks
 
Physics news on Phys.org
Firepanda said:
6789rl.png


I would have thought this would just be 2611 (in whatever units) for the expected time taken, does anyone know where the other two terms come from?

Should my expectation be drawn from some kind of distribution?

Thanks

You can view the process as a discrete-time renewal process, where a "renewal" occurs at time n if the last letter of "abracadabra" happens at time n. Following the logic in Feller, "Introduction to Probability Theory and Its Applications, Vol. I" (Wiley, 1968), pp. 323--328), let un = Pr{renewal occurs at time n}, and note that we have
[tex](1/26)^{11} = u_n + (1/26)^7 u_{n-7} + (1/26)^{10} u_{n-10}.[/tex]
The process is "aperiodic", so [itex]\lim_{n \rightarrow \infty} u_n = 1/\mu[/itex] exists, where μ is the mean time between renewals = mean time to first renewal. So, we have
[tex](1/26)^{11} = (1/\mu)[1 + (1/26)^7 + (1/26)^{10}],[/tex]
which gives you what you want. To really grasp what is going on you need to go and read Feller or some more modern books that deal with Renewal Theory.

Alternatively, you can set up a somewhat complicated Markov chain representation and compute a mean first-passage time. However, the renewal argument is much, much simpler---assuming you know what it is about in the first place.

RGV
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K
Replies
1
Views
2K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 2 ·
Replies
2
Views
929
  • · Replies 8 ·
Replies
8
Views
4K
Replies
1
Views
1K