### Artificial IntelligenceAIMA Exercises

This exercise explores the stationary distribution for Gibbs sampling methods.
1. The convex composition $[\alpha, q_1; 1-\alpha, q_2]$ of $q_1$ and $q_2$ is a transition probability distribution that first chooses one of $q_1$ and $q_2$ with probabilities $\alpha$ and $1-\alpha$, respectively, and then applies whichever is chosen. Prove that if $q_1$ and $q_2$ are in detailed balance with $\pi$, then their convex composition is also in detailed balance with $\pi$. (Note: this result justifies a variant of GIBBS-ASK in which variables are chosen at random rather than sampled in a fixed sequence.)
2. Prove that if each of $q_1$ and $q_2$ has $\pi$ as its stationary distribution, then the sequential composition $q q_1 \circ q_2$ also has $\pi$ as its stationary distribution.

This exercise explores the stationary distribution for Gibbs sampling methods.
1. The convex composition $[\alpha, q_1; 1-\alpha, q_2]$ of $q_1$ and $q_2$ is a transition probability distribution that first chooses one of $q_1$ and $q_2$ with probabilities $\alpha$ and $1-\alpha$, respectively, and then applies whichever is chosen. Prove that if $q_1$ and $q_2$ are in detailed balance with $\pi$, then their convex composition is also in detailed balance with $\pi$. (Note: this result justifies a variant of GIBBS-ASK in which variables are chosen at random rather than sampled in a fixed sequence.)
2. Prove that if each of $q_1$ and $q_2$ has $\pi$ as its stationary distribution, then the sequential composition $q q_1 \circ q_2$ also has $\pi$ as its stationary distribution.

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