6 citations · 6 across the 5 of their papers we have counts for
5 papers
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networks
Kevin Osanlou, Jeremy Frank, Andrei Bursuc +4
Planning under uncertainty is an area of interest in artificial intelligence. We present a novel approach based on tree search and graph machine learning for the scheduling problem…
Learning-based Preference Prediction for Constrained Multi-Criteria Path-Planning
Kevin Osanlou, Christophe Guettier, Andrei Bursuc +2
Learning-based methods are increasingly popular for search algorithms in single-criterion optimization problems. In contrast, for multiple-criteria optimization there are significa…
Time-based Dynamic Controllability of Disjunctive Temporal Networks with Uncertainty: A Tree Search Approach with Graph Neural Network Guidance
Kevin Osanlou, Jeremy Frank, J. Benton +4
Scheduling in the presence of uncertainty is an area of interest in artificial intelligence due to the large number of applications. We study the problem of dynamic controllability…
Learning off-road maneuver plans for autonomous vehicles
Kevin Osanlou
This thesis explores the benefits machine learning algorithms can bring to online planning and scheduling for autonomous vehicles in off-road situations. Mainly, we focus on typica…
Constrained Shortest Path Search with Graph Convolutional Neural Networks
Kevin Osanlou, Christophe Guettier, Andrei Bursuc +2
Planning for Autonomous Unmanned Ground Vehicles (AUGV) is still a challenge, especially in difficult, off-road, critical situations. Automatic planning can be used to reach missio…