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CAT Learning Algorithm Workbench (CLAW)

Award Information

Department of Defense
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Charles River Analytics Inc.
MA Cambridge, MA 02138-4555
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2012
Title: CAT Learning Algorithm Workbench (CLAW)
Agency / Branch: DOD / NAVY
Contract: N00024-12-P-4032
Award Amount: $149,979.00


Current countermeasure anti-torpedo (CAT) systems use explicit logic to direct intercepts resulting in an inability to adapt to the complexities of the stochastic marine environment. The CAT Learning Algorithm Workbench (CLAW) is an analytical research testbed capable of comparing the effectiveness of different machine learning approaches to optimize and automate anti-torpedo fire control and develop criteria concepts for discriminating among them. By applying recent developments in intelligent algorithms to existing simulations and models in the program of record using an instrumented test environment, investigators can identify the most promising designs for using adaptive learning in the Torpedo Warning System. The benefit of the approach is to harden battle group defenses against torpedo salvos by finding optimal fire control solutions and automating the launch decision process.

Principal Investigator:

Wayne Thornton
Senior Scientist
(617) 491-3474

Business Contact:

Mark Felix
Contracts Manager
(617) 491-3474
Small Business Information at Submission:

Charles River Analytics Inc.
625 Mount Auburn Street Cambridge, MA -

EIN/Tax ID: 042803764
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No