SBIR Phase II: Evolving Object Neural Networks

SBIR 第二阶段：进化对象神经网络

• 批准号: 0349604
• 负责人: David Fogel
• 金额: $ 49.96万
• 依托单位: NATURAL SELECTION, INCORPORATED
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-01 至 2006-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0349604&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Evolving; Object

This Small Business Innovation Research Phase II research project will investigate the problem of generating evolutionary object neural networks for controlling characters in classes of entertainment software, with consideration given to genres of massively multiplayer online games. The objective of the research is to identify and develop general self-adaptive routines and software tools that can be incorporated in a software developer's kit (SDK) that is suitable for licensing to third-party developers. A series of experiments conducted within a statistical framework will identify first- and second-order effects of parameter choices for the evolutionary control of game characters, which will be incorporated into the SDK. R&D will be aimed at generating the most rapid evolutionary learning for game characters while having the smallest code "footprint." Additional research will facilitate automatic play testing and optimization of artificial intelligence in games. The scientific and technical understanding of hybridizing evolutionary computation and neural networks will be enhanced by the careful study of the nonlinear effects of parameter choices in the studied settingsIf successful this product will ease the transition of video games from development to products. The development of an SDK that will help reduce the time and cost of segments of video game production by 50-80%. The software developed may serve as educational classroom aids in university courses. Furthermore, the strong correlation between video games and military simulations suggests important contributions to dynamic planning in combat simulations, as well as extensions to optimizing courses of action in business operations, such as supply-chain management.

本小企业创新研究第二阶段研究项目将研究生成进化对象神经网络的问题，以控制娱乐软件类中的角色，并考虑到大型多人在线游戏的类型。该研究的目的是确定和开发一般的自适应例程和软件工具，可以纳入一个软件开发工具包（SDK），适合许可给第三方开发人员。在统计框架内进行的一系列实验将确定游戏角色进化控制参数选择的一阶和二阶效应，这些效应将被纳入SDK。研发的目标是为游戏角色生成最快速的进化学习，同时拥有最小的代码“足迹”。“额外的研究将促进自动游戏测试和优化游戏中的人工智能。科学和技术的理解杂交进化计算和神经网络将加强通过仔细研究的非线性效应的参数选择在所研究的settingsIf成功的产品将缓解过渡的视频游戏从开发到产品。开发一个SDK，这将有助于减少视频游戏生产的时间和成本的50- 80%。所开发的软件可作为大学课程的教学辅助工具。此外，视频游戏和军事模拟之间的强相关性表明，它对作战模拟中的动态规划做出了重要贡献，并扩展到优化商业运营中的行动方案，如供应链管理。