Improving on Very Large Neighborhood Search techniques in Program Synthesis

Bachelor thesis (2022)

Authors

R. Hellinga Technology, Policy and Management

Contributors

S. Dumančić Algorithmics - EEMCS (mentor)
M.L. Molenaar Computer Graphics and Visualisation - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Rixt Hellinga
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Published Date

24-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Inductive Program Synthesis (IPS) has been implemented by a two-stage search algorithm, Brute, and consequently improved upon with a Large Neighborhood Search (LNS) technique, in an algorithm named Vlute. Unmotivated values and design choices within Vlute caused limitations on the performance of IPS tasks. This research improves upon several of these limitations through experiments. Most significant improvements are found in the robot-planning domain through the implementation of a stochastic accept method and a best improvement neighbor search.