1 / 58

Games

Games. Henry Kautz. ExpectiMiniMax: Alpha-Beta Pruning. Cutoffs at Max and Min nodes work just as before If range of values is bounded, can add cutoffs to Chance nodes Assume that all branches not searched have the worst-case result L = lowest value achievable (-10)

reed
Télécharger la présentation

Games

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Games Henry Kautz

  2. ExpectiMiniMax: Alpha-Beta Pruning Cutoffs at Max and Min nodes work just as before If range of values is bounded, can add cutoffs to Chance nodes Assume that all branches not searched have the worst-case result L = lowest value achievable (-10) U = highest value achievable (10)

  3. Values to come Values to come Values seen Values seen Current value Current value ExpectiMiniMax: Cutoffs • Alpha cutoff: • Beta cutoff:

  4. Probabilistic STRIPS Planning domain: Hungry Monkey shake: if (ontable) Prob(2/3) -> +1 banana Prob(1/3) -> no change else Prob(1/6) -> +1 banana Prob(5/6) -> no change jump: if (~ontable) Prob(2/3) -> ontable Prob(1/3) -> ~ontable else ontable

  5. What is the expected reward? [1] shake [2] jump; shake [3] jump; shake; shake; [4] jump; if (~ontable){ jump; shake} else { shake; shake }

  6. ExpectiMax

More Related