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公开(公告)号：US20140195475A1
公开(公告)日：2014-07-10
申请号：US14143410
申请日：2013-12-30
发明人： Georgiy Levchuk , Jared Freeman , Wayne Shebilske
IPC分类号： G06N7/00
摘要： Embodiments of this invention comprise modeling a subject's state and the influence of training treatments, or actions, on that state to create a training policy. Both state and effects of actions are modeled as probabilistic using Partially Observable Markov Decision Process (POMDP) techniques. Utilizing this model and the resulting training policy with subjects creates an effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy.
摘要翻译： 本发明的实施例包括对受试者的状态进行建模，以及训练治疗或动作对该状态的影响以创建训练策略。 动态的状态和效果都使用部分可观测马尔可夫决策过程（POMDP）技术进行建模。 利用这一模式和由此产生的培训策略为教师创造了有效的决策辅助，以提高相对于传统场景选择策略的学习。
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公开(公告)号：US20210142200A1
公开(公告)日：2021-05-13
申请号：US17101184
申请日：2020-11-23
发明人： Georgiy Levchuk , Jared Freeman , Wayne Shebilske
摘要： Embodiments of this invention comprise modeling a team's state and the influence of training treatments, or actions, on that state to create a training policy. Both state and effects of actions are modeled as probabilistic using Partially Observable Markov Decision Process (POMDP) techniques. Utilizing this model and the resulting training policy with teams creates an effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy.
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