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Implementing Artificial Thinking Autonomy with Model-Based System EngineeringComplex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration.

The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities.

This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy.

This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.
Document ID
20250000769
Acquisition Source
Stennis Space Center
Document Type
Conference Paper
Authors
Mitchell Kirshner
(University of Arizona Tucson, United States)
Fernando Figueroa
(Johnson Space Center Houston, United States)
Lauren W Underwood
(Stennis Space Center Bay Saint Louis, United States)
Date Acquired
January 21, 2025
Subject Category
Life Sciences (General)
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: 46th Annual IEEE Aerospace Conference
Location: Big Sky, MT
Country: US
Start Date: March 1, 2025
End Date: March 8, 2025
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
CONTRACT_GRANT: NXX12AJ48A
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
Professional Review
Keywords
Artificial Thought
Thinking Systems
Autonomous Thinking Systems
Autonomous Systems
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