3. Consider an undiscounted Markov decision process with three states 1, 2, 3, with respec-tive rewards -1, -2,0 for each visit to that state. In states 1 and 2, there are twopossible actions: a and b. The transitions are as follows:• In state 1, action a moves the agent to state 2 with probability 0.8 and makes theagent stay put with probability 0.2.In state 2, action a moves the agent to state 1 with probability 0.8 and makes theagent stay put with probability 0.2.. In either state 1 or state 2, action b moves the agent to state 3 with probability 0.1and makes the agent stay put with probability 0.9.Find the optimal policy that minimises the expected total cost and find the correspondingvalue function.

Write down the equations for the value function for each state and action. To do this, we use the…

Answered: Consider an undiscounted Markov…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Long-Run Properties of Markov Chains The leading brewery on the West Coast (labeled A) has hired an OR analyst to analyze its market position. It is particularly concerned about its major competitor (labeled B). The analyst -believes that brand switching can be modeled as a Markov chain using three states, with states A and B representing customers drinking beer produced from the aforementioned breweries and state C representing all other brands. Data are taken monthly, and the analyst has constructed the following (one-step) transition -matrix from past data. What are the steady-state market shares for the two major -breweries?
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Consider the Markov chain specified by the following transition diagram. a. Find the steady-state probabilities of all states. 0.4 b. If the initial state is 7, what is the expected 0.3 0.4 0.2 number of steps to reach state 1 or 3? 0.8 0.2 c. If at step 0 the system was in state 4, what is the probability that after step 3 it was in state 3 and after step 47 it was in state 3 again?
Suppose that a Markov chain has the following transition matrix The recurrent states are a A₁ A₂ A3 A4 A5 0 0 0 a₂000 P=a, 0 0 1 0 0 2 a 0 0 0 as 10000
A car rental company has two locations. Each week, 80% of the cars rented at location A are returned to location A and the rest location B. Of the cars rented at location B, 30% are returned to location B by the end of the week and the rest to location A. a. Make a transition diagram for this process. b. Write the transition matrix T for this process. cIf 50% of the company's cars start this week at location A, and 50% at location B, find the proportion of cars that will be at each location one week later Label your answers. d. Write and solve a system of equations to find the stable distribution (correct to 3 decimal places) for this Markov process. Show all calculations and label the row operations.
Using linear algebra principles for markov chain, how would I determine the equilibrium state of the the system to figure out how many DVDs would be at location P, Q, and R?
Anne and Barry take turns rolling a pair of dice, with Anne going first. Anne’s goal is to obtain a sum of 3, while Barry’s goal is to obtain a sum of 4. The game ends when either player reaches his goal,and the one reaching the goal is the winner. Define a Markov Chain to model the problem.
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A Markov system with two states satisfies the following rule. If you are in state 1 then of the time you change to state 2. If you are in state 2 then of the time you remain in state 2. state 1 Write the transition matrix for this system using the state vector v state 2 T = Find the long term probability (stable state vector). vs
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A state vector X for a four-state Markov chain is such that the system is three times as likely to be in state 4 as in 3, is not in state 2, and is in state 1 with probability 0.2. Find the state vector X.
In a hotel, each employee is in one of three possible job classifications, and changes that classifications (independently) according to a Markov chain with transition probabilities. What percentage of employees are in each classification?

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