We propose an architecture to enable the modular development and deployment of autonomous intelligent agents in support of spacecraft operations. This architecture supports both training and…
Ended Purchase Order Awarded Last action
- Contract number
- NNX17CJ26P
- Awardee
-
Onai Inc. UEI CLR5VEPH3MC1
- Awarding agency
-
Shared Services Center
National Aeronautics and Space Administration
- Obligated
- $111,758
Award facts
- Contract value 100% obligated
- $111,758.00 Current and potential, with all options
- Completion date 100% complete
- Current and potential, with all options
- NAICS code
- 541712 Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)
- Set-aside
- Total Small Business
- Competition
- Full and Open Competition after exclusion of sources · 500 offers Negotiated Proposal / Quote
- Pricing
- Firm Fixed Price
- Place of performance
- San Jose, CA 95129, USA
- Research
- SBIR Program Phase I Action
Award details come from SAM.gov/FPDS.
About this award
The National Aeronautics and Space Administration (NASA) Shared Services Center awarded a Small Business Innovation Research (SBIR) Program Phase I contract to Onai Inc., a minority-owned, for-profit organization based in San Jose, California. The $111,758.00 firm fixed-price contract is for the development of a cognitive architecture using reinforcement learning to enable autonomous spacecraft operations. The proposed architecture supports the modular development and deployment of autonomous intelligent agents for spacecraft operations, including both training and application of artificial intelligence models. Key deliverables include a preliminary cognitive architecture, a feasibility study, a prototype autonomous agent, and a detailed plan for a comprehensive cognitive architecture feasibility study.
Description
We propose an architecture to enable the modular development and deployment of autonomous intelligent agents in support of spacecraft operations. This architecture supports both training and application of artificial intelligence models. IT particularly enables the use of deep reinforcement learning for each module independently and jointly. Deep reinforcement learning is a technique that enables the automated learning of plans of action and has recently successfully been used, for example, to learn strategies for games like go. Our proposed architecture provides a "utility" layer for generalized learning and a provides for independent functional modules that can be added, modified, or removed easily. IT also accounts for intensive multicore computational needs. Lastly, IT allows for desired behavior to be learned independently or in the context of the broader system. In phase i, we will deliver a preliminary cognitive architecture, a feasibility study, a prototype of an autonomous agent, and a detailed plan to develop a comprehensive cognitive architecture feasibility study.
Quick answers
Who was awarded contract NNX17CJ26P?
NNX17CJ26P was awarded to Onai Inc. by Shared Services Center (National Aeronautics and Space Administration) on June 9, 2017.
How much is contract NNX17CJ26P worth?
The government has obligated $111,758 on NNX17CJ26P.
Was contract NNX17CJ26P competed?
The extent of competition for NNX17CJ26P was full and open competition after exclusion of sources. The government received 500 offers. It was set aside: Total Small Business.
On GovTribe
See this award's full record
- Every transaction and funding action
- The awardee's other awards and teaming partners
- Similar awards and recompete opportunities
- Ask GovTribe AI about this award