围棋系统的设计 含英文翻译.doc
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围棋系统的设计 含英文翻译,摘要本文通过对几个顶尖电脑围棋程序的研究，从认知科学的角度介绍了电脑围棋，并特别针对电脑围棋编程人员（或有意投身于此的程序员）说明围棋作为一 个认知科学研究领域的日益增长的重要性。对于手谈、go4++、many faces of go、go intellect 和explorer等几个目前最优秀的电脑围棋程序，我们概要...
内容介绍
此文档由会员 wanli1988go 发布
摘要
本文通过对几个顶尖电脑围棋程序的研究，从认知科学的角度介绍了电脑围棋，并特别针对电脑围棋编程人员（或有意投身于此的程序员）说明围棋作为一 个认知科学研究领域的日益增长的重要性。对于手谈、Go4++、Many Faces of Go、Go Intellect 和Explorer等几个目前最优秀的电脑围棋程序，我们概要介绍了这些程序所涉及的人工智能技术，不得不面对的关键性挑战和博弈树搜索所牵涉的问题，由 此揭示在围棋领域不能很好地移植计算机国际象棋技术的原因。
Abstract
Based on the number of top computer chess procedures from the perspective of cognitive science of computer chess. especially in computer chess programmers (or programmers who are interested in joining this) as one cognitive research shows Go the growing importance of the field. On hand for that Go4++, Many Faces of Go. Go Intellect Explorer and several of the most outstanding computer chess procedures We outline the procedures involved in artificial intelligence technology Game and had to face the critical challenges involved in the search tree. Go to reveal in this area by the transplant computer chess unable to technical reasons.
参考文献
Allis, V.Searching for solutions in games and artificial intelligence. PhD thesis, University of Limburg, Maastricht, 1994.
Burmeister, J.&Wiles, J. The challenge of Go as a domain for AI research: a comparison between Go and chess. In proceedings of the Third Australian and New Zealand Conference on Intelligent Information System, pages 181-186, Perth, November 1995. IEEE Western Australia Section.
Chen, K. Group Identification in Computer Go. In D.N.L.Levy and B.F.Beal, (eds), Heuristic Programming in Aritificial Intelligence: the First Computer Olympiad, pages 195-210. Ellis Horwood, Chichester, 1989.
Chen, K. The move decision process of Go Intellect. In David Erbach, editor, Computer Go, 14: 9-17, 1990.
Chen, K. Attack and defence. In H. J. Van den Herik and L. V. Allis,(ed)s, Heuristic Programming in Artificial Intelligence 3 - The Third Computer Olympiad, pages 146-156. Ellis Horwood, Chichester, 1992.
Donnelly, P., Corr, P., and Crookes, D. Evolving Go playing strategy in neurl networks, 1994. Available on the Internet at ftp://igs.nuri.net/Go/comp/egpsnn.ps.z.
Fotland, D. Knowledge representation in The Many Faces of Go,1993. Available on the Internet at ftp://igs.nuri.net/Go/comp/mfg.z.
Lishtenstein, D. & Sipser, M. Go is polynomial-space hard. Journal of the ACM, 27(2):393-401, 1980.
Muller, M. Computer Go as a sum of local games: an application of combinatorial game theory. PhD thesis, Swiss Federal Institute of Technology Zurich, 1995.
Pell, B. Exploratory learning in the game of Go. In D. N. L. Levy and D.F. F. Beal,(eds), Heuristic Programming in Artificial Intelligence 2 - The Second Computer Olympiad, volume 2. Ellis Horwood, 1991
Robson, J. The complexity of Go. In R. E. A. Mason, (ed), Proceedings of the IFIP 9th World Computer Congress, pages 413-417, North Holland, 1983. IFIP, Elsevier Science Publishers.
Ryder, J. Heuristic analysis of large trees as generated in the game of Go. Phd thesis, Department of Computer Science, Standford University, 1971.
Saito, Y. & Yoshikawa, A. Go as a testbed for Cognitive Science studies. In IJCAI Workshop Proceedings Using Games as an Experimental Testbed for AI Research, 1997.
Schraudolph, N., Dayan, P. and Sejnowski, T. Temporal difference learning of position eva luation in the game of Go. In J. D. Cowan, G. Tesauro and J. Alspector, (eds), Advances in Neural Information Processing 6, pages 817-824. Morgan Kaufmann, San Francisco, 1994.
Zorbrist, A. Amodel of visual organization for game Go. In Proceedings of the Spring Joint Computer Conference, 34: 103-112, 1969.
Zorbrist, A. Feature extractions and representation for pattern recognition and the game of Go. PhD thesis, Graduate School of the University of Wisconsin, 1970.
References
Allis. V.Searching for solutions in games and artific ial intelligence. PhD thesis, University of Limburg, Maastricht, 1994.
Burmeister, J.&Wiles. J. The challenge of Go as a domain for AI research : a comparison between chess and Go. In proceed ings of the Third Australian and New Zealand Con ference on Intelligent Information System , pages 181-186, Perth , November 1995. IEEE Western Australia Secti on.
Chen, K. Group Identification in Computer Go. In D.N. L.Levy and B.F.Beal, (eds). Heuristic Programming in Aritificial Intelli Contemporary : the First Computer Olympiad. pages 195-210. Ellis Horwood, Chichester, 1989.
Chen, K. The move decision process of Go Intellect. In David Erbach, editor, Computer Go, 14 : 9-17, 1990.
Chen, K. Attack and defense. In H. J. Van den Herik and L. V. Allis, (ed.) s, Heuristic Programming in Artificial Intellig in healthy 3 - The Third Computer Olympiad. pages 146-156. Ellis Horwood, Chichester, 1992.
Donnelly, P. , Corr, P. , And Crookes. D. Evolving Go playing strategy in neurl ne..
本文通过对几个顶尖电脑围棋程序的研究，从认知科学的角度介绍了电脑围棋，并特别针对电脑围棋编程人员（或有意投身于此的程序员）说明围棋作为一 个认知科学研究领域的日益增长的重要性。对于手谈、Go4++、Many Faces of Go、Go Intellect 和Explorer等几个目前最优秀的电脑围棋程序，我们概要介绍了这些程序所涉及的人工智能技术，不得不面对的关键性挑战和博弈树搜索所牵涉的问题，由 此揭示在围棋领域不能很好地移植计算机国际象棋技术的原因。
Abstract
Based on the number of top computer chess procedures from the perspective of cognitive science of computer chess. especially in computer chess programmers (or programmers who are interested in joining this) as one cognitive research shows Go the growing importance of the field. On hand for that Go4++, Many Faces of Go. Go Intellect Explorer and several of the most outstanding computer chess procedures We outline the procedures involved in artificial intelligence technology Game and had to face the critical challenges involved in the search tree. Go to reveal in this area by the transplant computer chess unable to technical reasons.
参考文献
Allis, V.Searching for solutions in games and artificial intelligence. PhD thesis, University of Limburg, Maastricht, 1994.
Burmeister, J.&Wiles, J. The challenge of Go as a domain for AI research: a comparison between Go and chess. In proceedings of the Third Australian and New Zealand Conference on Intelligent Information System, pages 181-186, Perth, November 1995. IEEE Western Australia Section.
Chen, K. Group Identification in Computer Go. In D.N.L.Levy and B.F.Beal, (eds), Heuristic Programming in Aritificial Intelligence: the First Computer Olympiad, pages 195-210. Ellis Horwood, Chichester, 1989.
Chen, K. The move decision process of Go Intellect. In David Erbach, editor, Computer Go, 14: 9-17, 1990.
Chen, K. Attack and defence. In H. J. Van den Herik and L. V. Allis,(ed)s, Heuristic Programming in Artificial Intelligence 3 - The Third Computer Olympiad, pages 146-156. Ellis Horwood, Chichester, 1992.
Donnelly, P., Corr, P., and Crookes, D. Evolving Go playing strategy in neurl networks, 1994. Available on the Internet at ftp://igs.nuri.net/Go/comp/egpsnn.ps.z.
Fotland, D. Knowledge representation in The Many Faces of Go,1993. Available on the Internet at ftp://igs.nuri.net/Go/comp/mfg.z.
Lishtenstein, D. & Sipser, M. Go is polynomial-space hard. Journal of the ACM, 27(2):393-401, 1980.
Muller, M. Computer Go as a sum of local games: an application of combinatorial game theory. PhD thesis, Swiss Federal Institute of Technology Zurich, 1995.
Pell, B. Exploratory learning in the game of Go. In D. N. L. Levy and D.F. F. Beal,(eds), Heuristic Programming in Artificial Intelligence 2 - The Second Computer Olympiad, volume 2. Ellis Horwood, 1991
Robson, J. The complexity of Go. In R. E. A. Mason, (ed), Proceedings of the IFIP 9th World Computer Congress, pages 413-417, North Holland, 1983. IFIP, Elsevier Science Publishers.
Ryder, J. Heuristic analysis of large trees as generated in the game of Go. Phd thesis, Department of Computer Science, Standford University, 1971.
Saito, Y. & Yoshikawa, A. Go as a testbed for Cognitive Science studies. In IJCAI Workshop Proceedings Using Games as an Experimental Testbed for AI Research, 1997.
Schraudolph, N., Dayan, P. and Sejnowski, T. Temporal difference learning of position eva luation in the game of Go. In J. D. Cowan, G. Tesauro and J. Alspector, (eds), Advances in Neural Information Processing 6, pages 817-824. Morgan Kaufmann, San Francisco, 1994.
Zorbrist, A. Amodel of visual organization for game Go. In Proceedings of the Spring Joint Computer Conference, 34: 103-112, 1969.
Zorbrist, A. Feature extractions and representation for pattern recognition and the game of Go. PhD thesis, Graduate School of the University of Wisconsin, 1970.
References
Allis. V.Searching for solutions in games and artific ial intelligence. PhD thesis, University of Limburg, Maastricht, 1994.
Burmeister, J.&Wiles. J. The challenge of Go as a domain for AI research : a comparison between chess and Go. In proceed ings of the Third Australian and New Zealand Con ference on Intelligent Information System , pages 181-186, Perth , November 1995. IEEE Western Australia Secti on.
Chen, K. Group Identification in Computer Go. In D.N. L.Levy and B.F.Beal, (eds). Heuristic Programming in Aritificial Intelli Contemporary : the First Computer Olympiad. pages 195-210. Ellis Horwood, Chichester, 1989.
Chen, K. The move decision process of Go Intellect. In David Erbach, editor, Computer Go, 14 : 9-17, 1990.
Chen, K. Attack and defense. In H. J. Van den Herik and L. V. Allis, (ed.) s, Heuristic Programming in Artificial Intellig in healthy 3 - The Third Computer Olympiad. pages 146-156. Ellis Horwood, Chichester, 1992.
Donnelly, P. , Corr, P. , And Crookes. D. Evolving Go playing strategy in neurl ne..
