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CASE-BASED SELECTION OF ALLOCATION METHODS

Award Information

Agency:
Department of Defense
Branch:
Army
Award ID:
12627
Program Year/Program:
1990 / SBIR
Agency Tracking Number:
12627
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
KLEIN ASSOC., INC.
1750 Commerce Center Blvd. North Fairborn, OH 45324
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1990
Title: CASE-BASED SELECTION OF ALLOCATION METHODS
Agency / Branch: DOD / ARMY
Contract: N/A
Award Amount: $55,452.00
 

Abstract:

THE OBJECTIVE IS TO DEVELOP A CASE-BASED REASONING (CBR) SYSTEM FOR DETERMINING THE ALLOCATION METHODS USED BY FIRE DIRECTION OFFICERS. CASE-BASED REASONING IS A NEW APPROACH TO EXPERT SYSTEMS; COMPARED TO RULE-BASED SYSTEMS, CBR APPEARS TO BE A MORE EFFICIENT, SENSITIVE, AND EFFECTIVE STRATEGY TO DERIVE AND REPRESENT CRITICAL KNOWLEDGE. PHASE I WILL DEMONSTRATE THE FEASIBILITY OF A CBR APPROACH THAT USES TACTICAL FIRE CONTROL DECISION DATA FROM PREVIOUS EXERCISES AS THE BASIS FOR PREDICTIONS. STANDARD ARTIFICIAL INTELLIGENCE (AI) APPROACHES RUN INTO THE DIFFICULTY OF HAVING TO MODEL THE COMPLEXITIES OF THE HARDWARE/SOFTWARE ELEMENTS ALONG WITH THE COMPLEXITIES OF THE HUMAN FACTORS. A CBR STRATEGY AVOID THIS PROBLEM BY RELYING ON MATCHES TO SIMILAR PROJECTS SO THAT IT IS NOT NECESSARY TO REPRESENT WORLD KNOWLEDGE. ADDITIONALLY, A CBR APPROACH OFFERS THE POSSIBILITY OF IMPROVING REAL-TIME PERFORMANCE CONSIDERABLY, SINCE A SIMILAR CASE REPRESENTING A NEAR SOLUTION CAN BE RETRIEVED RAPIDLY.

Principal Investigator:

Dr Gary A Klein
5137672691

Business Contact:

Small Business Information at Submission:

Klein Assocs Inc
Po Box 264 - 800 Livermore St Yellow Springs, OH 45387

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No