# Tag Info

2

Yes, in general any linear combination of probability distributions between optimal policies is also an optimal policy. In fact any combination with each state treated separately will also be an optimal policy. This can be seen using the equation for optimal deterministic policy in terms of optimal value function: \pi^*(s) = \text{argmax}_a [\sum_{r,s'}p(r,...

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Short answer Two policies are different if they take different actions in a specific state $s$ (or they give different probabilities of taking those actions in $s$). There can be more than one optimal policy for a given value function: this only happens when two actions have the same value in a given state. Nevertheless, both policies lead to the same ...

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It depends on the stopping condition. If the stopping condition is "stop as soon as any vertex is encountered by both the forward and backward scan", then bidirectional uniform-cost search is not a correct algorithm -- it is not guaranteed to output the optimal path. But it is possible to adjust the stopping condition to make bidirectional ...

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UCS is optimal (but not necessarily complete) Let's first recall that the uniform-cost search (UCS) is optimal (i.e. if it finds a solution, which is not guaranteed unless the costs on the edges are big enough, that solution is optimal) and it expands nodes with the smallest value of the evaluation function $f(n) = g(n)$, where $g(n)$ is the length/cost of ...

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