Read e-book online Computers and Games: 8th International Conference, CG 2013, PDF

By H. Jaap van den Herik, Hiroyuki Iida, Aske Plaat

ISBN-10: 3319091646

ISBN-13: 9783319091648

ISBN-10: 3319091654

ISBN-13: 9783319091655

This booklet constitutes the completely refereed post-conference complaints of the eighth overseas convention on desktops and video games, CG 2013, held in Yokohama, Japan, in August 2013, along with the seventeenth computing device and video games event and the 20 th global Computer-Chess Championship. The 21 papers offered have been rigorously reviewed and chosen for inclusion during this e-book. They disguise a variety of issues that are grouped into 5 sessions: Monte Carlo Tree seek and its improvements; fixing and looking; research of video game attribute; new ways; and severe games.

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Read Online or Download Computers and Games: 8th International Conference, CG 2013, Yokohama, Japan, August 13-15, 2013, Revised Selected Papers PDF

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Additional info for Computers and Games: 8th International Conference, CG 2013, Yokohama, Japan, August 13-15, 2013, Revised Selected Papers

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It consists of adding a bonus term in the UCB formula to take directly into account the 34 K. Ikeda and S. 5 2 UCB bonus CBT coefficient Fig. 4. Winning rate of Nomitan in function of the UCB bonus CBT coefficient value P (mj ) of the Bradley-Terry model described by Eq. 2. In a program that already contains a Bradley-Terry model for the simulation policy or for progressive widening, this is easy and immediate to implement. Formula 1 becomes: μj = wj +C · nj ln n + CBT · nj K · P (mj ) n+K (6) where CBT is the main coefficient to tune the effect (small or strong) of this bias, and K is a parameter that allows us to tune the rate at which the effect decreases.

CG 2013. LNCS, vol. 8427. Springer, Heidelberg (2014) 10. : Localizing search in Monte-Carlo go using statistical covariance. ICGA J. 32(3), 154–160 (2009) 11. : Current frontiers in computer Go. IEEE Trans. Comput. Intell. AI Games 2, 229–238 (2010) 12. : Reinforcement learning and simulation-based search in computer Go. D. thesis, University of Alberta (2009) 13. : Monte-Carlo simulation balancing. In: International Conference on Machine Learning, pp. 945–952 (2009). 14. : Density Estimation For Statistics and Data Analysis.

We use the number of hyperedges to indicate the memory size for DBH, and the number of searched moves to indicate the TSS tree size. Figure 8 shows the percentage of DBH size over TSS tree size for all testing positions. We can see that the ones with large TSS tree sizes usually have lower percentage of memory requirement for DBH. 6 Conclusion For Connect6 and other k-in-a-row games, DBS is critical for TSS when there are many independent or nearly independent TSS areas, a situation that is especially common during end game.

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Computers and Games: 8th International Conference, CG 2013, Yokohama, Japan, August 13-15, 2013, Revised Selected Papers by H. Jaap van den Herik, Hiroyuki Iida, Aske Plaat


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