Computer Go -- A Proxy for Key Open Challenges and Opportunities in Computational Intelligence

Computer Go——计算智能领域关键开放挑战和机遇的代表

• 批准号: 0725382
• 负责人: Donald Wunsch
• 金额: $ 30万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725382&HistoricalAwards=false
• 关键词: Computer; Go; Proxy; Key; Open

Proposal Number: 0725382Proposal Title: Computer Go -- A Proxy for Key Open Challenges and Opportunities in Computational IntelligencePI Name: Wunsch, Donald C.PI Institution: University of Missouri-RollaThe objective of this research is to illuminate and narrow the differences between computer and human capabilities by making a 9x9 Go player, and creating the groundwork for a 19 x 19 player. The approach is to: Combine Simultaneous Recurrent Networks with Cellular Neural Networks, and train them via Reinforcement Learning, to analyze influence functions; Create Neurofuzzy rules for known patterns; Compare approaches to move filtering; Develop improved tactical analysis; Bootstrap endgame techniques backwards; Develop optimized hardware; Perform outreach.The intellectual merit of the proposed research is: Go is much harder than Chess and its solution offers more to science. Its subtleties mirror core issues in learning. Creative and original concepts are proposed, as outlined in the approach section above. The PI and Co-PI have been collaborators since 1998, and both have significant research track records in many synergistic projects.The broader impacts of the proposed research are: Improved heuristics for cutting through combinatorial complexity. Creating stronger links between learning architectures and improving their training. Contributions to related applications:Economics, Security Applications, Sensor networks,Embedded systems,Biologically-inspired applications, K-12, international, and underrepresented groups outreach. The dissemination of results will be superior, due to the availability of Go rules and data. The project will benefit society, through an improved ability to automate strategic analysis, through better tools, and through an improved workforce.

提案编号：0725382提案标题：计算机围棋——计算智能中关键开放挑战和机遇的代理名称：Wunsch， Donald C.PI机构：密苏里大学罗拉本研究的目标是通过制作9x9的围棋选手，并为19x19的选手创造基础，来阐明和缩小计算机和人类能力之间的差异。方法是：将同步循环网络与细胞神经网络相结合，通过强化学习对其进行训练，分析影响函数；为已知模式创建神经模糊规则；比较移动过滤的方法；改进战术分析；引导游戏结束技巧；开发优化的硬件；执行推广。这项拟议研究的智力价值在于：围棋比国际象棋难得多，其解决方案提供了更多的科学依据。它的微妙反映了学习的核心问题。如上面的方法部分所述，提出了创造性和原创性的概念。自1998年以来，PI和Co-PI一直是合作伙伴，并且在许多协同项目中都有重要的研究记录。所提出的研究的更广泛的影响是：改进了通过组合复杂性切割的启发式。在学习架构和改进培训之间建立更强的联系。对相关应用的贡献：经济学，安全应用，传感器网络，嵌入式系统，生物启发应用，K-12，国际和代表性不足的群体外展。由于围棋规则和数据的可用性，结果的传播将是优越的。通过提高战略分析自动化的能力，通过更好的工具，通过改进的劳动力，该项目将使社会受益。