论文标题
基于因素的决策能力自我评估框架
A Factor-Based Framework for Decision-Making Competency Self-Assessment
论文作者
论文摘要
我们总结了我们迄今为止的努力，以开发一个框架，以基于机器自信心，即机器人在完成指定任务的功能能力方面的自信心，即机器人的自信心。尽管早期工作探索了机器以适当的方式进行利基应用程序，但我们的分解机器自信框架引入并结合了概率元元推理的几个方面，用于算法计划和决策，以使其不确定，以使一系列可用于竞争的自信心因素，以支持竞争性的自信心因素，以支持竞争力的评估，以评估各种各样的问题。
We summarize our efforts to date in developing a framework for generating succinct human-understandable competency self-assessments in terms of machine self confidence, i.e. a robot's self-trust in its functional abilities to accomplish assigned tasks. Whereas early work explored machine self-confidence in ad hoc ways for niche applications, our Factorized Machine Self-Confidence framework introduces and combines several aspects of probabilistic meta reasoning for algorithmic planning and decision-making under uncertainty to arrive at a novel set of generalizable self-confidence factors, which can support competency assessment for a wide variety of problems.
