Efficiency in Policy Optimization Implementation
Evaluate the colleague's suggestion. If the log Z(x) term is removed, how will this change affect (a) the final optimal parameters θ found after training, and (b) the overall efficiency of the training process? Justify your reasoning.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
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Solution to KL Divergence Minimization for Policy Optimization
When optimizing a policy π_θ to match an optimal policy π*, the objective function is often simplified from Objective A to Objective B:
Objective A:
arg min_θ Eₓ[KL(π_θ(·|x) || π*(·|x)) - log Z(x)]Objective B:arg min_θ Eₓ[KL(π_θ(·|x) || π*(·|x))]What is the fundamental mathematical reason this simplification is valid?
Efficiency in Policy Optimization Implementation
Justification for Simplification in Policy Optimization