1 / 19

Generalized Threats Search

Generalized Threats Search. Paper Review Paper Author: T. Cazenave Review by: A. Botea. Overview. Motivation Generalized Threats Generalized Threats Search (GTS) Experimental Results Conclusion. Motivation. Threat Search works well in games such as Go or Go-Moku GTS:

sanaa
Télécharger la présentation

Generalized Threats Search

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. Generalized Threats Search Paper Review Paper Author: T. Cazenave Review by: A. Botea

  2. Overview • Motivation • Generalized Threats • Generalized Threats Search (GTS) • Experimental Results • Conclusion

  3. Motivation • Threat Search works well in games such as Go or Go-Moku • GTS: • Generalizes the previously published threat algorithms (Abstract Proof Search, Lambda Search, Iterative Widening, Gradual Abstract Proof Search); • Can be faster than other threat algorithms;

  4. Generalized Trees • Binary trees where players can play multiple moves in a row • Two players: Left & Right • Left branches are Left’s moves • Right branches are Right’s moves

  5. Generalized Threats (GTs) • Generalized Threat: • A set of generalized trees with some special properties • Can be represented as tuples: oi = #of nodes followed by at most i left branches

  6. Examples of GTs

  7. Comparison of GTs • Partial order relationship:

  8. Comparison of GTs (2)

  9. Composition of GTs

  10. Composition of GTs (2)

  11. Verification of GTs • Map GT to a concrete move tree so that Left wins • Check that: • For each left branch there is a winning Left move • For each right branch there are no Right moves that prevent Left from winning • The local search used to verify a GT can be optimized

  12. Optimizing GT verification • At nodes that have left branches only: iterative widening • At nodes with both left and right branches: divide-and-conquer • Use abstract moves • Ex. from Atari-Go: if Right strings have >2 liberties, 2-ply search won’t work

  13. Generalized Threat Search • Alpha-Beta • Use GTs to speed-up search • Forced moves for Right • Ex: move 2 found by a (4,3,0) GT • Forced moves for Left • Ex: move 5 found by a (3,2,0) GT

  14. Example

  15. Experimental Results • Atari-Go on a 6x6 board • Compare: • Alpha-Beta • Lambda Search • Gradual Abstract Proof Search • Generalized Threats Search

  16. Experimental Results

  17. Experimental Results

  18. Experimental Results

  19. Conclusion • Generalized Threat Search: • More general than other threat search algorithms • Also faster • Applied to 6x6 Atari-Go • Future Work: try GTS in other games such as Go, LoA, Phutball, Hex, Shogi, and Chess

More Related