发明名称 |
PROBABILISTIC DECISION MAKING SYSTEM AND METHODS OF USE |
摘要 |
Embodiments of this invention comprise modeling a subject's state and the influence of training scenarios, 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. The POMDP is well suited to decision-theoretic planning under uncertainty. Utilizing this model and the resulting training policy with real world subjects creates a surprisingly effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy. POMDP provides a more valid representation of trainee state and training effects, thus it is capable of producing more valid recommendations concerning how to structure training to subjects.
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申请公布号 |
US2011016067(A1) |
申请公布日期 |
2011.01.20 |
申请号 |
US20090921755 |
申请日期 |
2009.03.11 |
申请人 |
APTIMA, INC.;WRIGHT STATE UNIVERSITY |
发明人 |
LEVCHUK GEORGIY;FREEMAN JARED;SHEBLINSKI WAYNE |
分类号 |
G06F15/18 |
主分类号 |
G06F15/18 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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