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An Open Boundary Safety-of-Territory Solver for the Game of Go

This paper presents the Open Boundary Safety-of-Territory Solver 2.0 for the game of Go, which estimates the safety of open boundary territories. The solver includes new features such as customized search goals, multi-searches, and integration with full-board play. Experimental results show the solver's effectiveness in evaluating the safety status of open boundary areas. Future work includes implementing a flexible time control scheme, integrating other tactical solvers, and measuring playing strength improvements.

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An Open Boundary Safety-of-Territory Solver for the Game of Go

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  1. An Open Boundary Safety-of-Territory Solver for the Game of Go Author: Xiaozhen Niu, Martin Mueller Dept of Computing Science University of Alberta Presented by: Xiaozhen Niu

  2. Outline • Introduction • Open Boundary Safety-of-Territory Solver • Forward Pruning Techniques • Experimental Results • Conclusions and Future Work

  3. Introduction • Problem: In real games, most territories are not fully enclosed • Safety solver 1.0 has several restrictions: • The region has to be completely enclosed • Does not consider external liberties • Goal: estimating the safety of open boundary territories!

  4. Example • White plays first

  5. Open Boundary Safety-of-Territory Solver • New features of safety solver 2.0 • Input parameters and goal setting • Board partitioning • Multiple searches for related goals

  6. New Features • Safety solver 2.0 has following new features: • Search goals customized by different parameters • Multi-searches to provide solutions for different goals • Integration with full-board play in Explorer

  7. Input parameters (1) • A set of points (area) • The color of the defender and attacker • The color of the first player • Boundary safe or territory safe?

  8. Input parameters (2) • Handle Seki • External Liberties • Who is the ko winner?

  9. Search Goal Setting • Safety solver 2.0 concentrates on proving area safe locally • Does not consider connection problems • Default search goal: • Prove territory safe • Handle seki • Count external liberties • No ko winner needs to be set initially

  10. Board Partitioning • Zone computing • Zone merging

  11. Zone Computing • Use heuristic territory evaluation to partition the board into zones • Zones are computed by using dividers, potential dividers

  12. Zone Merging • Two zones are related if they share one or more common boundary blocks • Safety solver 2.0 extends the merging algorithm for enclosed zones by dealing with dividers

  13. Example

  14. Multiple Searches for Related Goals • Switching which player plays first

  15. Multiple Searches for Related Goals (2) • Determining when external liberties affect the safety status of an area

  16. Integration with Explorer • Generate defending or invading move for zones • Set move values by heuristics

  17. Forward Pruning Techniques • Two techniques for the defender: • External moves • Inner eyes

  18. External Moves • In a 12 interior points zone. Generate 20 moves for the attacker and 16 moves for the defender

  19. Inner Eyes • Inner eyes can be pruned for the defender

  20. Experimental Results • Two test sets. • Set one: most from classic Guan Zi Pu. 60 main problem and 60 modified problems that has some external liberties added • Set two: 20 problems from computer game play records

  21. Test Set 1: Correctness Test • Four Examples from set 1

  22. Test Set 2: Game Play Test • Goal: to test whether Explorer enhanced by the safety solver 2.0 is able to play the correct defending or invading move

  23. Conclusions • Safety solver 2.0 can provide evaluations for the safety status of open boundary areas • Major limitation: size of the open area (current: 15)

  24. Future Work: • Flexible time control scheme using heuristics to select suitable problems to solve • Get best try move • Integrate other tactical solvers • Measure playing strength improvements

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