Given the scenario below, calculate the advantage of the agent's chosen action and explain what the resulting value signifies about the performance of that specific action.

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The Advantage Function, $$A(s_t, a_t)$$, measures the relative benefit of taking a specific action $$a_t$$ in a state $$s_t$$ compared to the expected value from that state onward. It is calculated by subtracting the state-value function, $$V(s_t)$$, which acts as a baseline ($$b$$), from the sum of future rewards. The formula is: $$A(s_t, a_t) = \sum_{k=t}^{T} r_k - V(s_t)$$

Advantage Function Formula

Evaluating an Action's Performance

An agent in a given state `s` takes an action `a`. The sequence of rewards it receives from that point until the end of the episode sums to a total of 10. The pre-calculated value for state `s`, representing the average expected sum of future rewards from that state, is 15. Based on this information, what can be concluded about the action `a`?

An agent is in a specific situation where the average expected sum of future rewards is +2. The agent tries two different actions on separate occasions. After taking Action 1, the actual sum of future rewards it receives is +5. After taking Action 2, the actual sum of future rewards is -10. For which action is the 'advantage' value higher, and what does this value signify about that action's quality relative to the average expectation from that situation?

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