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EasyCog: Affordable and Easy to Develop Cognitive Models

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-10-C-0281
Agency Tracking Number: N091-086-0321
Amount: $497,342.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N091-086
Solicitation Number: 2009.1
Timeline
Solicitation Year: 2009
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-03-30
Award End Date (Contract End Date): 2011-09-29
Small Business Information
625 Mount Auburn Street
Cambridge, MA -
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Peter Weyhrauch
 Senior Scientist
 (617) 491-3474
 pweyhrauch@cra.com
Business Contact
 Ninos Hanna
Title: Contract Specialist
Phone: (617) 491-3474
Email: nhanna@cra.com
Research Institution
N/A
Abstract

Applications that incorporate human behavior models (HBMs) have the potential to improve the training, decision-making, and even the operational effectiveness of US forces. This software can mimic human decision-making, reasoning, learning, social and cultural biases, as well as perceptual, cognitive, and motor limitations in support of many applications, including analysis, simulation-based acquisition, training, and mission rehearsal. Unfortunately, the development of such complex software systems is currently costly, time consuming, and error-prone due to a lack of appropriate high-level languages and corresponding development tools. To improve the affordability, efficiency and robustness of the HBM-development process, we propose to design and demonstrate the feasibility of EasyCog, a high-level cognitive language, development environment, and compiler that is designed to improve the HBM-development process across multiple cognitive architectures. EasyCog combines cognitive, behavioral, social, affect and cultural models with high-level programming language features to improve the breadth and scalability of HBMs. Visual editors and debuggers work at the level of the high-level language to improve the efficiency of model development. Finally, EasyCog can generate configurable source code for a variety of existing cognitive architectures, meaning runtime users can reuse models in a variety of domains based on a single high-level model.

* Information listed above is at the time of submission. *

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