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Action-Value Function Definition
The action-value function, often referred to as the Q-value function, evaluates the anticipated return an agent will accumulate by starting in a specific state , executing a particular action , and then strictly adhering to a given policy for all subsequent decisions.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Bellman Equation
State-Value Function (V) Formula
An agent is in a state
sand must choose between two actions:AandB. According to the agent's current policy, it chooses actionAwith a 70% probability and actionBwith a 30% probability. The expected total future reward for taking actionAfrom statesis +20. The expected total future reward for taking actionBfrom statesis -10. Based on this information, which of the following statements correctly describes the relationship between the value of being in statesand the values of taking each action?An agent is learning to navigate a complex environment. Match each of the following questions the agent might have with the type of value function that would most directly provide the answer.
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Action-Value Function Definition
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Advantage Function in Terms of Q-values and V-values
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Action-Value Function Formula
An agent is learning to play a game where the goal is to maximize its final score. At a specific point in the game (a 'state'), the agent is considering several possible moves ('actions'). A function is used to estimate the total expected future score that can be achieved by taking a specific action from the current state and then playing optimally for the rest of the game. What does the output of this function represent for a given state-action pair?
Utility of Action-Specific Value Estimation
Choosing the Right Tool for Decision-Making