# Maximum Entropy

This is actually super useful and practical, because the world is full of Uncertainty.

The Entropy is given by $H(X)=−∑_{x∈X}p(x)gp(x)$

This is another way to formulate. To take into account uncertainty, so for Robustness.

$V=max_{π(a)}(E[r(a)]+βH(π(a)))$

We use Constrained Optimization to come up with a set of equations.

This is a really important derivation

ahh you want to maximize entropy so that the policy is not as deterministic

Max-entropy Value Iteration $V_{k}(s)=max_{π}(E[R(s,a)+V_{k−1}(s_{′})]+βH(π(a∣s)))$