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How is policy iteration different from value iteration?
The policy iteration algorithm updates the policy. The value iteration algorithm iterates over the value function instead. Still, both algorithms implicitly update the policy and state value function in each iteration. In each iteration, the policy iteration function goes through two phases.
Is value iteration a planning algorithm?
Since Value Iteration as part of Dynamic Programming requires full knowledge of the environment, it is indeed a planning algorithm.
What is the value iteration algorithm?
Value iteration is a method of computing an optimal MDP policy and its value. Saving the V array results in less storage, but it is more difficult to determine an optimal action, and one more iteration is needed to determine which action results in the greatest value.
What is the value of iteration?
Value iteration is a method of computing an optimal MDP policy and its value. = maxa Qk(s,a) for k>0. It can either save the V[S] array or the Q[S,A] array.
What is the difference between value iteration and policy iteration?
In policy iteration algorithms, you start with a random policy, then find the value function of that policy (policy evaluation step), then find a new (improved) policy based on the previous value function, and so on. In this process, each policy is guaranteed to be a strict improvement over the previous one (unless it is already optimal).
Is the max operation ommited in policy iteration?
In policy iteration (PI), this max operation is ommited in step 1 (policy evaluation) by just following the intermediate policy to choose the action.
How are policy evaluation and policy extraction similar?
The algorithms for policy evaluation and finding optimal value function are highly similar except for a max operation (as highlighted) Similarly, the key step to policy improvement and policy extraction are identical except the former involves a stability check.