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Based on the policy: Figure out which squares can be reached from b3 after two sequential actions under this policy with what probabilities. Note: make sure the summation of all probabilities is 1.

Based on the policy: Figure out which squares can be reached from b3 after two sequential actions under this policy with what probabilities. Note: make sure the summation of all probabilities is 1.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Based on the policy:

  1. Figure out which squares can be reached from b3 after two sequential actions under this policy with what probabilities. Note: make sure the summation of all probabilities is 1.
  2. Figure out which squares can be reached from b3 after all possible number of sequential actions under this policy (no probability calculation is needed).
Environment for the following four questions: We consider a windy maze as shown in the following figure with probabilistic outcomes after an action. All surroundings and the black square are walls. The terminal states are at Square a4 with a reward +100 and Square b4 with a reward -100. The agent can drift to the left or the right (with respect to the directional action) with probability 0.1 respectively and go straight with probability 0.8. If the drifting direction is a wall, it will be bounced back to the original position. It can be modeled as a MDP. -100 a +100 1 2 3 4 We consider the policy defined in the following table. C -100 a +100 1 2 4
Transcribed Image Text:Environment for the following four questions: We consider a windy maze as shown in the following figure with probabilistic outcomes after an action. All surroundings and the black square are walls. The terminal states are at Square a4 with a reward +100 and Square b4 with a reward -100. The agent can drift to the left or the right (with respect to the directional action) with probability 0.1 respectively and go straight with probability 0.8. If the drifting direction is a wall, it will be bounced back to the original position. It can be modeled as a MDP. -100 a +100 1 2 3 4 We consider the policy defined in the following table. C -100 a +100 1 2 4
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