KBR Wyle Services, LLC — Department of Defense SBIR Phase II: A16-043
KBR Wyle Services, LLC — SBIR Phase II award from Department of Defense.
Phase II SBIR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- Obligated amount $999,999 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
- Topic code A16-043 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $999,999
- Agency
- Department of Defense · Army
- Program / Phase
- SBIR · Phase II
- Topic
- A16-043
- Solicitation
- 2016.0
- NAICS
- —
- Place of performance
- OH
- Period
- 2017-09-30 → 2019-09-29
Description
Our proposed COllection Management Planning using Agent Surrogates (COMPAS) Phase II program includes a talented, multi-disciplined team led by experts in software agent technology, decision support tools, and in the Military Decision Making Process. Phase I resulted in a distributed multi-agent system solution to support intelligence collection management by determining the best collection of military resources/assets to be used for a set of collection tasks defined by a planner. Our solution was achieved through lightweight belief/desire/intention agents that are given a set of goals that allowed them to solve a Constraint Satisfaction Problem using a small set of base ontology objects as domain constraints. These results are presented in a four-dimensional display allowing the operator to readily assess intelligence tasking, resources, and locations in relation to one another and the related Priority Information Requirements. Phase II will include extending this work by improving the performance of the software agents constraint solving capabilities and increasing the quality of the base level ontology. In addition, to better match real world use cases, we will increase our focus on the individual planning agent allowing a single agent to optimize resources rather than a global optimization across all planners.