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Both these algorithms keeps generating random neighbors and picks if it encounters a neighbor with a better state than current. So where lies the difference?

It is mentioned everywhere, First Choice Hill Climbing is suitable for cases with many successors. But really, whats the difference?

Also, In the link:

Stochastic hill climbing vs first-choice hill climbing algorithms

It is mentioned that First choice picks the first random move and stochastic picks a move which is given randomly. Don't see the implementation difference still. Please help.

Ritu Raj
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  • Possible duplicate of [Stochastic hill climbing vs first-choice hill climbing algorithms](https://stackoverflow.com/questions/38825027/stochastic-hill-climbing-vs-first-choice-hill-climbing-algorithms) – Md. Abu Nafee Ibna Zahid Mar 04 '18 at 05:20

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In first choice hill climbing, it will choose the first found of a better state. For example, if current state has 10,000 neighbors from search spaces. And the current state found a better state of a neighbor after several or first visit then it will choose it immediately.

In stochastic hill climbing, it is not always first to be chosen. For example when the particular state found 5 better neighbors/solutions after several visits/generated neighbor or solution, then randomly choose from them based on probability by how far the current state with the new better solution.

Gusti Ahmad Fanshuri Alfarisy
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