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in AI and Deep Learning by (50.2k points)

I am a little confused about the Hill Climbing algorithm. I want to "run" the algorithm until I found the first solution in that tree ( "a" is initial and h and k are final states ) and it says that the numbers near the states are the heuristic values. Here's the tree:

enter image description here

My question: I am trying to run hill climbing on the tree, so ok we start a-> f-> g and then what ?? finish(without result), but I read that hill climbing can't go back and make a new choice(example j or e)? Is that right? If I can go back then how? I mean where we change our initial choice example we choose e instead of g or j instead of f

Sorry if my question is too simple.

1 Answer

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by (108k points)

It’s a very simple technique that allows us to algorithmize finding solutions:

  • Define the current state as an initial state

  • Apply any possible operation on the current state and generate a possible solution

  • Compare the newly generated solution with the goal state

  • If the goal is achieved or no new states can be created, quit. Otherwise, return to step 2

It works very well with simple problems. As it is an exhaustive search, it is not feasible to consider it while dealing with large problem spaces. It is also known as the British Museum algorithm (trying to find an artifact in the British Museum by exploring it randomly).

It is also the main idea behind the Hill-Climbing Attack in the world of biometrics. This approach can be used for generating synthetic biometric data.

You can refer the following link for the implementation of Hill-Climbing:

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