知觉限制下的可验证自主性

Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems Pub Date : 2021-05-18 DOI:10.1145/3459086.3459635

U. Topcu

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引用次数: 0

摘要

最近一组将形式化方法、凸优化和机器学习相结合的算法，在可能具有不确定转移概率的部分可观察马尔可夫决策过程的验证和综合的可扩展性方面提供了数量级的改进。

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Verifiable autonomy under perceptual limitations

A recent set of algorithms in the intersection of formal methods, convex optimization and machine learning offers orders-of-magnitude improvement in the scalability of verification and synthesis in partially observable Markov decision processes possibly with uncertain transition probabilities.

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Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems

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