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klderivation [2024/12/24 12:48] – [Assumption 2: Restrictions on the cost function] pedroortega | klderivation [2024/12/24 12:58] (current) – [Connecting to the free energy objective] pedroortega | ||
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===== Assumption 2: Restrictions on the cost function ===== | ===== Assumption 2: Restrictions on the cost function ===== | ||
- | Next, we'll impose constraints on the cost function. We want our cost function to capture efforts that are structurally consistent with the underlying probability space. (Later, we'll see how to relax these assumption | + | Next, we'll impose constraints on the cost function. We want our cost function to capture efforts that are structurally consistent with the underlying probability space. (Later, we'll see how to relax these assumptions |
{{ :: | {{ :: | ||
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===== Cost of deliberation ===== | ===== Cost of deliberation ===== | ||
- | Now, let's calculate the cost of transforming the prior choice probabilities into posterior choice probabilities: | + | Now, based on our sketch above, let's calculate the cost of transforming the prior choice probabilities into posterior choice probabilities: |
\[ | \[ | ||
\begin{align} | \begin{align} | ||
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We've obtained two expectation terms. The second is proportional to the Kullback-Leibler divergence between of the posterior to the prior choice probabilities. What is the first expectation? | We've obtained two expectation terms. The second is proportional to the Kullback-Leibler divergence between of the posterior to the prior choice probabilities. What is the first expectation? | ||
- | The first expectation represents the expected cost of each individual choice. This is because each term $C(x \cap d|x \cap c)$ measures the cost of transforming the relative probability of a specific choice. | + | The first expectation represents the expected cost of each individual choice |
===== Connecting to the free energy objective ===== | ===== Connecting to the free energy objective ===== | ||
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We can transform the above equality into a variational principle by replacing the individual choice costs $C(x \cap d|x \cap c)$ with arbitrary numbers. The resulting expression is convex in the posterior choice probabilities $P(x|d)$, so we get a nice and clean objective function with a unique minimum. | We can transform the above equality into a variational principle by replacing the individual choice costs $C(x \cap d|x \cap c)$ with arbitrary numbers. The resulting expression is convex in the posterior choice probabilities $P(x|d)$, so we get a nice and clean objective function with a unique minimum. | ||
- | We can even go a step further: | + | We can even go a step further: |
\[ | \[ | ||
\sum_x P(x|d) U(x) - \frac{1}{\beta} \sum_x P(x|d) \log \frac{ P(x|d) }{ P(x|c) }. | \sum_x P(x|d) U(x) - \frac{1}{\beta} \sum_x P(x|d) \log \frac{ P(x|d) }{ P(x|c) }. |