APPLICATION OF BLACK-BOX OPTIMIZATION ON SYSTEM VERIFICATION

Leung, Peter

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https://hdl.handle.net/2142/125084 Copy

Description

Title

APPLICATION OF BLACK-BOX OPTIMIZATION ON SYSTEM VERIFICATION

Author(s)

Leung, Peter

Issue Date

2020-05-01

Keyword(s)

Verification; Optimistic Optimization; Black-box; DryVR

Abstract

System verification is a very generalizable problem about ensuring how a system behaves. Reliable system verification techniques are essential as autonomous systems are becoming more prevalent. This can be seen with increasing numbers of self-driving cars and drone deliveries. Our research approaches this problem by determining if a system is safe. In other words: Given the possible states from different initial conditions, do all these states avoid a predefined unsafe set? We have set up a method to utilize optimization techniques to help verify systems. Our research focuses on black-box verification, where we can only take zero-order evaluations of the function in question. There is already much research into problems where we have full knowledge of the function to be optimized, or no knowledge at all. But limited work has been done in the area in between. We hope to leverage some knowledge of the “smoothness” of the function to help us verify systems. This thesis explains how we set up these systems and utilized previous research on optimistic optimization. The thesis proposes a new optimization algorithm. Lastly results are compared to suggest what systems and conditions would be best suited to each algorithm, or whether an approach entirely different from ours would be more appropriate.

Type of Resource

text

Language

eng

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