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Plan Learning Across Textual Observations (PLATO) Phase II

Award Information
Agency: Department of Defense
Branch: Defense Threat Reduction Agency
Contract: HDTRA119C0010
Agency Tracking Number: T162-004-0096
Amount: $999,870.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: DTRA162-004
Solicitation Number: 16.2
Solicitation Year: 2016
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-11-01
Award End Date (Contract End Date): 2021-02-28
Small Business Information
2435 N. Central Expressway Suite 1200
Richardson, TX 75080
United States
DUNS: 127802234
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Mohler
 Senior Scientist
 (972) 231-0052
Business Contact
 Finley Lacatusu
Phone: (972) 231-0052
Research Institution

In Phase II of PLATO, we will develop a prototype plan and goal identification system that employs a rich model of domain actions and events, extracted automatically from a massive amount of real-world domain-relevant information, to model agent-specific action costs and to process sequences of agent actions and events, extracted from text, as an agent plan in progress. The system will be able to (1) model the inferential knowledge of preconditions, effects, and quantities associated with domain actions and events, derived from web-scale textual resources; (2) extract and structure domain-relevant agent actions and states from text for incorporation into an explorable knowledge base; (3) model action costs for a particular agent in a variety of dimensions including financial cost, legal and moral constraints, and educational requirements; (4) perform goal identification over agent event sequences by estimating agent distance to a goal through state-of-the-art planning; and (5) provide visualization and exploratory methods for users to identify agent capabilities, likely ‘next steps’, and high-level steps within an agent plan.

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

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