Language Models are Spacecraft Operators
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909155634184192 |
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| author | Rodriguez-Fernandez, Victor Carrasco, Alejandro Cheng, Jason Scharf, Eli Siew, Peng Mun Linares, Richard |
| author_facet | Rodriguez-Fernandez, Victor Carrasco, Alejandro Cheng, Jason Scharf, Eli Siew, Peng Mun Linares, Richard |
| contents | Recent trends are emerging in the use of Large Language Models (LLMs) as autonomous agents that take actions based on the content of the user text prompts. We intend to apply these concepts to the field of Guidance, Navigation, and Control in space, enabling LLMs to have a significant role in the decision-making process for autonomous satellite operations. As a first step towards this goal, we have developed a pure LLM-based solution for the Kerbal Space Program Differential Games (KSPDG) challenge, a public software design competition where participants create autonomous agents for maneuvering satellites involved in non-cooperative space operations, running on the KSP game engine. Our approach leverages prompt engineering, few-shot prompting, and fine-tuning techniques to create an effective LLM-based agent that ranked 2nd in the competition. To the best of our knowledge, this work pioneers the integration of LLM agents into space research. Code is available at https://github.com/ARCLab-MIT/kspdg. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_00413 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Language Models are Spacecraft Operators Rodriguez-Fernandez, Victor Carrasco, Alejandro Cheng, Jason Scharf, Eli Siew, Peng Mun Linares, Richard Space Physics Artificial Intelligence Machine Learning Recent trends are emerging in the use of Large Language Models (LLMs) as autonomous agents that take actions based on the content of the user text prompts. We intend to apply these concepts to the field of Guidance, Navigation, and Control in space, enabling LLMs to have a significant role in the decision-making process for autonomous satellite operations. As a first step towards this goal, we have developed a pure LLM-based solution for the Kerbal Space Program Differential Games (KSPDG) challenge, a public software design competition where participants create autonomous agents for maneuvering satellites involved in non-cooperative space operations, running on the KSP game engine. Our approach leverages prompt engineering, few-shot prompting, and fine-tuning techniques to create an effective LLM-based agent that ranked 2nd in the competition. To the best of our knowledge, this work pioneers the integration of LLM agents into space research. Code is available at https://github.com/ARCLab-MIT/kspdg. |
| title | Language Models are Spacecraft Operators |
| topic | Space Physics Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2404.00413 |