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[ author_sort:"chen, mo." ]
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High Dimensional Reachability Analys...
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Chen, Mo.
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High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification./
作者:
Chen, Mo.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
167 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Contained By:
Dissertation Abstracts International79-05B(E).
標題:
Artificial intelligence. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10607827
ISBN:
9780355576726
High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.
Chen, Mo.
High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 167 p.
Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Thesis (Ph.D.)--University of California, Berkeley, 2017.
Automation is becoming pervasive in everyday life, and many automated systems, such as unmanned aerial systems, autonomous cars, and many types of robots, are complex and safety-critical. Formal verification tools are essential for providing performance and safety guarantees for these systems. In particular, reachability analysis has previously been successfully applied to small scale control systems with general nonlinear dynamics under the influence of disturbances. Its exponentially scaling computational complexity, however, makes analyzing more complex, large scale systems intractable. Alleviating computation burden is in general a primary challenge in formal verification.
ISBN: 9780355576726Subjects--Topical Terms:
516317
Artificial intelligence.
High Dimensional Reachability Analysis: Addressing the Curse of Dimensionality in Formal Verification.
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Automation is becoming pervasive in everyday life, and many automated systems, such as unmanned aerial systems, autonomous cars, and many types of robots, are complex and safety-critical. Formal verification tools are essential for providing performance and safety guarantees for these systems. In particular, reachability analysis has previously been successfully applied to small scale control systems with general nonlinear dynamics under the influence of disturbances. Its exponentially scaling computational complexity, however, makes analyzing more complex, large scale systems intractable. Alleviating computation burden is in general a primary challenge in formal verification.
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This thesis presents ways to tackle this "curse of dimensionality" from multiple fronts, bringing tractable verification of complex, practical systems such as unmanned aerial systems, autonomous cars and robots, and biological systems closer to reality. The theoretical contributions pertain to Hamilton-Jacobi (HJ) reachability analysis, with applications to unmanned aerial system. In addition, this thesis also explores two frontiers of HJ reachability by combining the formal guarantees of reachability with the computational advantages of optimization and machine learning, and with fast motion planning algorithms commonly used in robotics. The potential and benefits of the theoretical advances are demonstrated in numerous practical applications.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10607827
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