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Inside HARUKA

Inside HARUKA. Written by Ryuichi Kawa Surveyed by Akihiro Kishimto. Obstacles to Go-Playing Programs. So many exceptions that must be implemented: E.g. A & B are connected, B & C are connected, but A & C aren’t Static evaluation v.s. search If possible, evaluate statically

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Inside HARUKA

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  1. Inside HARUKA Written by Ryuichi Kawa Surveyed by Akihiro Kishimto

  2. Obstacles to Go-Playing Programs • So many exceptions that must be implemented: • E.g. A & B are connected, B & C are connected, but A & C aren’t • Static evaluation v.s. search • If possible, evaluate statically • If exceptions frequently appears, perform a search

  3. Overview of HARUKA’s Search Engine • 6 routines • Fuseki • Joseki • Life and death • Semeai • Search around center • Local search • Each routine returns move and evaluation value called deiri(input/output) computation • Compute value by my playing first • Compute value by opponent playing first • Compute 1. – 2. And return this value

  4. Fuseki Routine • Inaccurate but looks stable with occasional adjustments • Each fuseki move has evaluation values: • Three-four point, star point: 18 points • Kakari: 17 points • Corner enclosure: 16 points • Extension, splitting move etc: 8-15 points based on distance and strength of stones

  5. Joseki Routine • Pattern sized 11 * 11 • Immediately makes a move if pattern matches • Randomly choose one if more than one pattern matches • Pattern matches with smaller sizes (9 * 9 or 7 * 7) • Regard as promising move • Passed to local search engine

  6. Life and Death/Semeai Routines • Return status (e.g. win, win for Ko, seki) of life and death/semeai • Occasionally returns incorrect outcome • E.g. stones outside of region influences on outcome • Might be only a part of local search engine?

  7. Search around Center • Perform 3-ply search for points extending/fighting/breaking moyo around center of the board • # of branches <= 10 • Choose point that doesn’t contain any stones for 8 directions • Prepared for programs playing like Go++ • Currently does not work well

  8. Overview of Local Search • Search range • (x,y): stone worth considering • R = {(p,q)| |p – x| + |q – y| < 8} • Ladder is an exception • Alpha-beta search • Maximum number of branches = 10 • Depth = direct 3-5 ply search • Spends almost all the time

  9. Overview of Local Search (cont’d) • How is a local search performed? • Do a local search around the opponent’s stone played last time • Do a local search around the stone I played last time • Compute places that are influenced on by these two stones • Perform local searches around these places • Previous results are stored and updated • Re-searches are performed if necessary

  10. Position Recognition (1 / 3) • From simple notion to complicated (19 features) • Whether there’s a stone or not, # of empty stones around a point, ko point • Strings and # of stones, liberties (up to 4) , # of liberties • Characteristics of connections • 1-point jump, 2-point jump, knight’s move, knight’s big move • Detect points where opponent can’t cut • kosumi, bamboo, eye, opponent’s suicide point • Points where ate/nuki is possible • Points where cut/fukurami is possible

  11. Position Recognition (2 / 3) • Status on whether white and black stones are adjacent • Points for connections (1-point jump peep, keima-dekiri), double atari • Capture search • Kiri(cut) search (reuse capture search) • Life and death for semi-connected strings and influence computation • Eye-shape (eye, half-eye, eye with 2 (3, 4, ..) consecutive moves, false-eye)

  12. Position Recognition (3 / 3) • Detect groups • Compute boundary and size of moyo for each group • Compute how easily group can be escaped and connection to other groups • Strength, size and importance of group • Compute evaluation values for moves played at the points adjacent to stones • hane, nobi, attach, ate,cut, tsuki-nuke, pincer-attach, etc • Compute evaluation values for moves played at the points not adjacent to stones • 1-point jump, kosumi, keima-gake, hazama, sarusuberi, etc

  13. Capture Search • Alpha-beta search + TT for string with # of liberties <= 4 • # of branches <= 8 • Depth <= 64 • # of node limit <= 1000 • Performs well if # of liberties <= 3 • Needs a lot of time (sometimes 90% of computation) to determine outcome • Cannot distinguish unconditional capture from capture for ko • Need to restrict moves and prove strings aren’t captured as quickly as possible

  14. Kiri Search • Detect whether target strings are cut at cutting points • Utilize capture search • Stones dropped at cutting points are captured  target strings are not cut • Perform only at important points (capture search too) • points around stone played in the previous move

  15. Influence Computation • Preliminary compute life and death (strength) of stones • Compute influence: c / d^2 • c: strength of stone d: distance • Influenced up to 1-point jump point • Can’t go through other stones and bamboo • Add up these numbers

  16. Strength and Importance of Groups • Convert features into # of eye points • # of eye points • Eye-shape • Possibility to escape, extend, and connect • Status of opponent’s stones

  17. Evaluating Points (Not) Adjacent to Stones • Have value between 0 – 255 tuned by hand • 0: completely bad move • 64: bad move • 128: normal move • … • Used if all the stones in the region are (mostly) alive

  18. Move Generation • Moves are generated in the following order: • Moves having a high priority • connecting stones around stone played by opponent just before, escaping from atari, 2-line block • Double atari, capture, escape • Semeai moves • Attacking/defending weak stones • Moves at points (not) adjacent to stones having high evaluation values • Ko threats • Look at the whole board

  19. Evaluation at Leaf Nodes • Position recognition • Verifying if one of two strings can be captured • Detecting Life and death status for group • Adjusting life and death status for group considering connections to other groups • Adjusting life and death status for group considering opponent’s groups and semeai • Territory computation

  20. Other Issues • Adjustment to search results • Adding 1-4 points for sente move • Effective for yose

  21. Near Future Work • Play moves that prevents opponent’s moyo • Adjust evaluation values for yose considering double-sente, sente, double-gote • Have a strategy for detecting a loss • Perform 5-ply search without degrading speed (realization probability?) • Improve capture search

  22. Things that Must be Done in the Long Run • Strategies based on position evaluation • There’s no difference of losses between 0.5 point and 100 points • Human-like playing style • Consistency, moves when in a disadvantageous position • Special scheme for ko fights • Seems to be impossible with searches only

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