dc.contributor.author | Guttulsrud, Håkon | |
dc.contributor.author | Sandnes, Mathias | |
dc.contributor.author | Shrestha, Raju | |
dc.date.accessioned | 2024-02-29T07:30:19Z | |
dc.date.available | 2024-02-29T07:30:19Z | |
dc.date.created | 2024-02-28T18:23:15Z | |
dc.date.issued | 2024 | |
dc.identifier.isbn | 979-8-4007-0798-8 | |
dc.identifier.uri | https://hdl.handle.net/11250/3120376 | |
dc.description.abstract | Efficient space travel requires intelligent and robust control
mechanisms during spacecraft landing scenarios. Developing a
control mechanism for a rocket trajectory problem is inherently
complex. This paper introduces a novel approach using Deep
Q-Learning (DQL) with Short-Term Memory (STM) to address
the intrinsic challenges of this task. Unlike traditional Q-Learning
methods, our DQL STM agent performs in an environment with
uncertainties such as starting position, gravity, and wind in both
training and simulation, allowing for enhanced robustness in
difficult environmental conditions. This adaptation enables the
agent to observe 𝑛�-previous state-action pairs, offering a more
accurate estimation of environmental dynamics. Experiments
demonstrate that this new approach yields better results under
stricter testing conditions compared to previous methods. Moreover,
we establish the innovative aspects of our methodology through
systematic comparisons with basic Q-Learning, highlighting the
merits of the DQL STM agent. | en_US |
dc.language.iso | eng | en_US |
dc.relation.ispartof | ICCPR '23: Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition | |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Solving the Lunar Lander Problem with Multiple Uncertainties using a Deep Q-Learning based Short-Term Memory Agent | en_US |
dc.type | Chapter | en_US |
dc.description.version | acceptedVersion | en_US |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 2250765 | |
dc.source.pagenumber | 27-33 | en_US |