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  2. Hill climbing - Wikipedia

    en.wikipedia.org/wiki/Hill_climbing

    In simple hill climbing, the first closer node is chosen, whereas in steepest ascent hill climbing all successors are compared and the closest to the solution is chosen. Both forms fail if there is no closer node, which may happen if there are local maxima in the search space which are not solutions.

  3. Min-conflicts algorithm - Wikipedia

    en.wikipedia.org/wiki/Min-conflicts_algorithm

    In fact, Constraint Satisfaction Problems that respond best to a min-conflicts solution do well where a greedy algorithm almost solves the problem. Map coloring problems do poorly with Greedy Algorithm as well as Min-Conflicts. Sub areas of the map tend to hold their colors stable and min conflicts cannot hill climb to break out of the local ...

  4. Beam search - Wikipedia

    en.wikipedia.org/wiki/Beam_search

    Conversely, a beam width of 1 corresponds to a hill-climbing algorithm. [3] The beam width bounds the memory required to perform the search. Since a goal state could potentially be pruned, beam search sacrifices completeness (the guarantee that an algorithm will terminate with a solution, if one exists).

  5. Iterated local search - Wikipedia

    en.wikipedia.org/wiki/Iterated_local_search

    Iterated Local Search [1] [2] (ILS) is a term in applied mathematics and computer science defining a modification of local search or hill climbing methods for solving discrete optimization problems. Local search methods can get stuck in a local minimum, where no improving neighbors are available.

  6. Google researchers claim new breakthrough in getting AI to ...

    www.aol.com/finance/google-researchers-claim...

    It then passes the problem to a different AI model, Google DeepMind’s AlphaZero, which was developed in 2017 and originally used to learn to play the strategy board games chess, go, and shogi at ...

  7. Stochastic hill climbing - Wikipedia

    en.wikipedia.org/wiki/Stochastic_hill_climbing

    Stochastic hill climbing is a variant of the basic hill climbing method. While basic hill climbing always chooses the steepest uphill move, "stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphill move." [1]

  8. Local search (constraint satisfaction) - Wikipedia

    en.wikipedia.org/wiki/Local_search_(constraint...

    A drawback of hill climbing with moves that do not decrease cost is that it may cycle over assignments of the same cost. Tabu search [1] [2] [3] overcomes this problem by maintaining a list of "forbidden" assignments, called the tabu list. In particular, the tabu list typically contains only the most recent changes.

  9. Microsoft sinks, chipmakers climb as AI rally faces divide - AOL

    www.aol.com/news/microsoft-sinks-chipmakers...

    Microsoft shares fell 2.4% on Wednesday as growth in the tech giant's cloud business slowed, while Nvidia and other chipmakers rallied following a bright quarterly report from Advanced Micro Devices.

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