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Macroscopic Understanding of the Game Situations in GO

Macroscopic Understanding of the Game Situations in GO. Toshihiko Yokogawa, Junju Nishino, Yuichi Mizuno. Dept. of Computer Science and Information Engineering National Dong Hwa University Reporter : Jung-Yun Lo. Outline. Introduction FOG System Understanding of “ Atsumi ” Example

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Macroscopic Understanding of the Game Situations in GO

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  1. Macroscopic Understanding of the Game Situations in GO Toshihiko Yokogawa, Junju Nishino, Yuichi Mizuno Dept. of Computer Science and Information Engineering National Dong Hwa UniversityReporter:Jung-Yun Lo

  2. Outline • Introduction • FOG System • Understanding of “Atsumi” • Example • Conclusion

  3. Introduction • Human players uses terms “thick (Atsui)”, “thin (Usui)”, “heavy (Omoi)”, “light (Karui)” to judge the situations • Thickness is the complex concept based on the strength and power width of stone groups • Propose that “thickness” is expresses by 2 dimensions, the power width from stone groups and their strength

  4. FOG System • FOG (Fuzzy Oriented Go) FOG FOE OrientationsResult of Fuzzy Inference EGO’s dataEGO’s status EGO

  5. FOG System EGO Do elementary procedureof Go Wait for opponent move Do next move Selection of next move Put “ready” to FOEand waitfor orientation Do some actions by orientations from FOE and wait for next orientation until “continue” from FOE Wait for “ready” from EGO Infer by fuzzy rules with getting information from EGO Put results to EGO Put “continue”to EGO FOE

  6. Understanding of “Atsumi” • Human players always consider “atsumi” and “usumi” in deciding a next move to use the stones most effectively • ATSUMI: Thickness, power or strength. Refers to a group with strong shape and few or no cutting points • Refers to stones with a powerful shape • Refers to having superior outward influence • Refers to having a lead in territory

  7. Influence for understanding of “atsumi” • Energy Source • From the wall of Gun • Energy Function • Energy Depression • Energy at a point in the fields of the Game • Point belongs to no Guns is calculated energy is represented as each sum of the same color groups

  8. Strength for understanding of “atsumi” • Human players’ understanding of strength • A Gun with no less than two perfect eyes, in other word, a Gun perfectly alive, is strong • A Gun with many processed eyes is strong • A Gun with wide spaces with some tight linkage is strong • A Gun with more than one linkage possibility with other strong Guns is strong • A Gun with more Dames is strong. A Dame means an unoccupied adjacent points of a stone

  9. Strength for understanding of “atsumi” • Considering neighboring stones • If an opponent strong Gun is near the considered Gun, its strength is weakened • If an ally strong Gun is near the considered Gun, its strength is strong

  10. Strength for understanding of “atsumi” • Elements of strength • Gankei • Largesse of territory • Tightness of linkage • Number of dame

  11. Strength for understanding of “atsumi” • When Gankei value exists, the basic strength is Gankei based and modified by TBS and DBS • When the area is eider than 6, the basic strength is width based and modified by linkage tightness

  12. Strength for understanding of “atsumi” • When a Gun has only one stone, the basic strength is Dame based and modified by height • Else, the basic strength is tightness based

  13. Understanding “atsumi” of an area based on strength and energy • “atsumi” of an area is defined by the strengths and distance of the neighboring Guns and the energy sum of each color

  14. Understanding of importance of an Area • Importance of an area is decided by rules using strength of Guns, distance between them, and the energies in the central points of the area

  15. Example Situation and candidates Guns, their walls and largesse Energy at the points

  16. Conclusion • By this method… • the situations of the game in Go can be totally understood and expressed by language-based expressions • Understood situations can be applied to language rules to express strategy. So we can write strategic rules similar to human players

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