Bsc Thesis - Multi-Objective Optimization for Artificial Intelligence Systems using Interactive User Approach (i.e., Preference Elicitation) - Aditi Mishra

Bachelor Thesis by Aditi Mishra

A Multi-Objective Optimization problem focuses on producing optimal paths considering different objectives. This project aims at developing optimal paths for disabled citizens in the city of Amsterdam by capturing their preferences, thus integrating an Interactive User Approach. This project builds on previous research, which utilizes a non-parametric approach, Gaussian Process with Expected Improvement, and, instead, provides a parametric approach, Bayesian Logistic Regression with Thompson Sampling, to tackle the problem. This research incorporates Thompson Sampling as the sampling method for exploration-exploitation trade-off.

The experiments conducted in this paper demonstrate that Thompson Sampling is slow in performance given its stochastic nature, and the parametric approach performs at par with the nonparametric approach. Hence, the results of the experiments suggest that approaching the problem with the use of a parametric approach is a promising method due to its advantage of maintaining performance and offering reusability.


This research was conducted by Aditi Mishra from the Department of Advanced Computing Sciences - Faculty of Science and Engineering, Maastricht University in collaboration with the AI Team, Urban Innovation and R&D, City of Amsterdam.

Involved civil servants: Diederik M. Roijers and Shayla Jansen

Supervisors: Diederik M. RoijersShayla Jansen

Image credits

Header image: Header Aditi