SBIR Phase II: Evolving Object Neural Networks

这个小型企业创新研究第二阶段的研究项目将研究生成进化对象神经网络的问题，以控制娱乐软件中的角色，并考虑到大型多人在线游戏的类型。研究的目的是确定和开发通用的自适应例程和软件工具，这些例程和软件工具可以合并到软件开发人员工具包（SDK）中，适合授权给第三方开发人员。在统计框架内进行的一系列实验将确定参数选择对游戏角色进化控制的一级和二级影响，这将被整合到SDK中。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”。进一步的研究将促进自动游戏测试和优化游戏中的人工智能。对混合进化计算和神经网络的科学和技术理解将通过对所研究设置中参数选择的非线性效应的仔细研究得到加强。如果该产品成功，将简化电子游戏从开发到产品的过渡。开发一个SDK，这将有助于减少50-80%的电子游戏制作时间和成本。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，视频游戏对战斗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。

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.