How Does Random Reset Impact Expected Distance in a Random Walk?

steps away from the starting point x=0 within n seconds (t) for a person who, at t=0, is standing on x=0 and every one second (t=t+1) moves to the right (x=x+1) in probability of 1/4, moves to the left (x=x-1) in probability of 1/4, and returns to x=0 in probability of 1/2."
  • #1
RsMath
7
0
If we have a person who in t=0 (time) is standing on x=0 .
every one second (t=t+1) in without any dependency on previous steps :
he moves to right(x=x+1) in probability = 1/4
and he moves to left (x=x-1) in probability = 1/4 .
and he goes back to x=0 in probability = 1/2 .

show that within n seconds (t) he never be more than O(logn) steps away from x=0 (start point) .

now I know how to solve a similar question : only he moves to right in prob=1/2 and to left in prob=1/2 (with chernoff bound) but the above question I don't know how to start ..

can anyone help me ?
thanks
 
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  • #2
RsMath said:
show that within n seconds (t) he never be more than O(logn) steps away from x=0 (start point) .

This is clearly not true. He can be as many as n steps away from x = 0, with nonzero probability. Do you mean "on average"?
 
  • #3
yes , I meant expectation(average)

"show that the expected maximum distance is not greater than O(logn)
 

FAQ: How Does Random Reset Impact Expected Distance in a Random Walk?

1. What is a random walk?

A random walk is a mathematical concept that describes the path of a randomly moving object or variable. In a random walk, each step is taken in a random direction, resulting in a path that is unpredictable and non-deterministic.

2. How is probability related to random walks?

Probability is closely related to random walks because it can be used to predict the likelihood of different outcomes in a random walk. The concept of probability is essential in understanding the behavior of random walks and determining the expected outcomes.

3. What is the difference between a discrete and continuous random walk?

A discrete random walk involves a series of random steps taken at specific intervals, while a continuous random walk involves a continuous sequence of random steps. Discrete random walks are often used to model events that occur in a finite amount of time, while continuous random walks are used for events that occur over an infinite period.

4. What are some real-life applications of random walks and probability?

Random walks and probability have applications in many different fields, including finance, biology, physics, and computer science. Some examples include predicting stock prices, modeling the movement of molecules, and simulating the spread of diseases.

5. How can random walks be used to study the behavior of complex systems?

Random walks can be used to model and study the behavior of complex systems by simulating the interactions and movements of individual components within the system. This allows scientists to make predictions about the overall behavior and patterns of the system, which can be helpful in understanding and managing complex systems.

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