Preference Guided Iterated Pareto Referent Optimisation for Accessible Route Planning

Computer Science > Artificial Intelligence [Submitted on 1 Apr 2026] Preference Guided Iterated Pareto Referent Optimisation for Accessible Route Planning Paolo Speziali, Arno De Greef, Mehrdad Asadi, Willem Röpke, Ann Nowé, Diederik M. Roijers We propose the Preference Guided Iterated Pareto Referent Optimisation (PG-IPRO) for urban route planning for people with different accessibility requirements and preferences. With this algorithm the user can interact with the system by giving feedback on a route, i.e., the user can say which objective should be further minimized, or conversely can be relaxed. This leads to intuitive user interaction, that is especially effective during early iterations compared to information-gain-based interaction. Furthermore, due to PG-IPRO's iterative nature, the full set of alternative, possibly optimal policies (the Pareto front), is never computed, leading to higher computational efficiency and shorter waiting times for users. Subjects: Artificial Intelligence (cs.AI); Machine Learning (cs.LG) Cite as: arXiv:2604.00795 [cs.AI]   (or arXiv:2604.00795v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2604.00795 Focus to learn more Submission history From: Paolo Speziali [view email] [v1] Wed, 1 Apr 2026 12:05:48 UTC (2,548 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.LG References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)