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Ryan O’Connor

Student

Project Title

Leveraging machine learning for the design and analysis of optimisation algorithms

Project Description

Combinatorial optimization problems arise in many areas of computer science and other disciplines, such as business analytics, artificial intelligence and operations research. These problems typically involve finding groupings, orderings or assignments of discrete, finite sets of elements that satisfy certain conditions or constraints. Designing good optimization algorithms requires human ingenuity and a spark of genius. Automating the process of designing and analyzing algorithms has been a long-standing quest for AI researchers and such techniques are expected to have a very high impact in a range of applications. This PhD thesis will explore if machine learning techniques (particularly reinforcement learning and graph neural networks) can be leveraged to augment the human ability to design good heuristics for given input distributions. The thesis will also explore if reinforcement learning techniques can assist in finding counterexamples to discover the limitations of the existing heuristics in terms of the best approximation ratio achievable or in terms of running time. The success of this project will greatly augment the human ability to design algorithms for combinatorial optimization problems in industry. 39