ROBOLEAP Publications Publications
ROBOLEAP Journal Papers
Pajarinen, J.; Thai, H.L.; Akrour, R.; Peters, J.; Neumann, G. (2019). Compatible natural gradient policy search, Machine Learning (MLJ), 108, 8, pp.1443--1466, Springer. Download Article BibTeX Reference
ROBOLEAP Conference and Workshop Papers
Lauri, M.; Pajarinen, J.; Peters, J. (2019). Information gathering in decentralized POMDPs by policy graph improvement, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
Download Article BibTeX Reference
Akrour, R.; Pajarinen, J.; Neumann, G.; Peters, J. (2019). Projections for Approximate Policy Iteration Algorithms, Proceedings of the International Conference on Machine Learning (ICML).
Download Article BibTeX Reference
Hoelscher, J.; Koert, D.; Peters, J.; Pajarinen, J. (2018). Utilizing Human Feedback in POMDP Execution and Specification, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
Download Article BibTeX Reference
ROBOLEAP Books, Book Chapters & Theses
Schotschneider, A. (2020). Learning High-Level Behavior for Autonomous Vehicles, Master Thesis.
BibTeX Reference
Hartmann, V. (2019). Efficient Exploration using Value Bounds in Deep Reinforcement Learning, Master Thesis.
Download Article BibTeX Reference
Zhi, R. (2018). Deep reinforcement learning under uncertainty for autonomous driving, Master Thesis.
Download Article BibTeX Reference
