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Full-Text Articles in Probability
Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis
Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis
Modeling, Simulation and Visualization Student Capstone Conference
This paper presents a probabilistic approach to quantifying interceptability of an interaction scenario designed to test collision avoidance of autonomous navigation algorithms. Interceptability is one of many measures to determine the complexity or difficulty of an interaction scenario. This approach uses a combined probability model of capability and intent to create a predicted position probability map for the system under test. Then, intercept-ability is quantified by determining the overlap between the system under test probability map and the intruderβs capability model. The approach is general; however, a demonstration is provided using kinematic capability models and an odometry-based intent model.
An Adaptive Algorithm For `The Secretary Problem': Alternate Proof Of The Divergence Of A Maximizer Sequence, Andrew Benfante, Xiang Xu
An Adaptive Algorithm For `The Secretary Problem': Alternate Proof Of The Divergence Of A Maximizer Sequence, Andrew Benfante, Xiang Xu
OUR Journal: ODU Undergraduate Research Journal
This paper presents an alternate proof of the divergence of the unique maximizer sequence {π₯β π} of a function sequence {πΉπ(π₯)} that is derived from an adaptive algorithm based on the now classic optimal stopping problem, known by many names but here βthe secretary problemβ. The alternate proof uses a result established by Nguyen, Xu, and Zhao (n.d.) regarding the uniqueness of maximizer points of a generalized function sequence {ππ,π π } and relies on the strict monotonicity of πΉπ(π₯) as π increases in order to show divergence of {π₯β π}. Towards this, limits of the exponentiated Gaussian CDF are β¦