I was reading a paper on Addressing function approximation Error in Actor critic methods where they explain a benefit of their proposed method as follows:
I wish to build an intuition of this effect with either a proof or an example. Thank you
2026-04-04 06:01:21.1775282481
How does expected minimum of a set of random variables decreases as the variance of the random variables increases?
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As an example, think of two distributions (RVs) with the same mean. If distribution 1 has a larger variance than distribution 2, the data will be more spread out. Distribution 1 will likely have a smaller minimum and a larger maximum than distribution 2 because its values tend to be further from the mean.