Math Problem Statement
In a simple MDP, an agent is in a state s, and the actions it can take can lead to the following outcomes: • With probability 0.4, the agent transitions to state , with reward , and 5 IIT KHARAGPUR AI4ICPS I HUB FOUNDATION Hands-on Approach to AI, Cohort-2, July – October 2024 Assignment 7: Reinforcement Learning ϵ s′ R = 10 v(s′) = • With probability 0.6, the agent transitions to state , with reward , and 3. The discount factor is 0.5. Using Bellman equation, find the expected value of state . s′′ R = 2 v(s′) = γ s
Solution
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Math Problem Analysis
Mathematical Concepts
Markov Decision Process (MDP)
Bellman Equation
Expected Value Calculation
Formulas
Bellman equation for state-value function
Theorems
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Suitable Grade Level
Advanced undergraduate level
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