ARTIFICIAL INTELLIGENCE STEERING GROUP TRIP REPORT

• Document Type: CREST
• Collection: General CIA Records
• Document Number (FOIA) /ESDN (CREST): CIA-RDP86M00886R000500050006-9
• Release Decision: RIPPUB
• Original Classification: U
• Document Page Count: 62
• Document Creation Date: December 21, 2016
• Document Release Date: August 22, 2008
• Sequence Number: 6
• Publication Date: May 10, 1984
• Content Type: REPORT

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UNCLASSIFIED
The Director of Central Intelligence
Washington, D.C. 20505
Intelligence Research &
Development Council
ARTIFICIAL INTELLIGENCE STEERING GROUP
TRIP REPORT
DATE/PLACE
10 May 1984
MITRE Corporation
McLean, Virginia
AISG
STAT
In lieu of our May meeting, the AI Steering Group visited the
Washington C3I Operations of MITRE Corporation:--.:.in McLean,
Virginia. The all-day session consisted of presentations,
demonstrations, and discussions of several MITRE AI projects of
potential interest to the Intelligence Community. The visit was
hosted by Mr. George Steeg, Chief Engineer of MITRE's C31
Operations activity. An agenda is attached.
The first speaker, described and demonstrated STAT
the ANALYST system, a prototype expert system for intelligence
fusion and situation assessment. The ANALYST system employs three
-UNCLASSIFIED
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levels of reasoning involving Tactical Intelligence Reports, Order
of Battle Information, and Analysis of Critical Indicators. It uses
(incomplete) information from COMINT, ELINT, and IMINT in a common
report format. The system operates with the Battlefield Environment
Model, an object-oriented simulation (written in ROSS on the VAX) in
which all units act according to some pre-established doctrine.
MITRE has invested 10 staff-years in develo in the ANALYST
system, and so far it has 120 "rules." stimated that STAT
an operating version might grow to 1500 rules which would require
moving the system from a VAX to a 2MB Lisp Machine. The system has
a menu-oriented user interface and can ask the user to supply data
and confidence factors. The mathematics of how to combine
confidence factors most effectively is still under consideration.
There is a rule editor to facilitate adding or changing rules and an
explanation capability to explain how the system arrived at an
answer. A set of viewgraphs is attached. More detail is available
from MITRE in a report on ANALYST: MTP-83W00002, February 1984.
talk addressed the subject of Military STAT
Planning. Planning systems generally are characterized by:
A hierarchy of plans
Deferred time ordering
Introspection and modification of plans
Deferred introduction of constraints.
Military planning (and to a large extent business planning) is
characterized by:
No "right" plan
Not able to choose the "best" plan
Unknown constraints and data
Erroneous constraints and data
"Commander's prerogative."
MITRE has developed a"system for logistics planning, but it, like
most automated planning efforts, suffers the following deficiencies:
Cannot produce partial plans
Difficult to trace the results of following a plan
Untimely response
Hard to check= plans
Not able to develop concurrent plans
Difficult to modify plans or monitor their execution.
MITRE has an IRAD project underway to address these deficiencies
using an AI approach. They are using a joint military operation
scenario which has been supplied by the Armed Forces Staff College.
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UNCLASSIFIED
Dr. Benoit suggested that there maybe intelligence applications of
this planning approach in the area of indications and warning
(either to detect deviations from an expected scenario or to fit a
behavorial model to the observed data).
discussed human factors in conjunction with the STAT
design of expert systems. While acknowledging the importance of
human factors issues in designing the end-user interface, Dr. Stech
focused his talk on the process of knowledge acquisition and the
need to systematically question knowledge before it g into a
system. Several methods and tools were described and STAT
emphasized a process called "chunking" of knowledge. Experiments
have verified that chess masters "chunk" situation reports about a
chess board status that enables them to reproduce a game board
rapidly and accurately. MITRE is investigating how tactical
analysts perceive a situation map and is setting up an analogous set
of experiments to determine the key features of a map that an expert
focuses on. A set of viewgraphs is attached.
next discussed the subject of photo STAT
interpretation and demonstrated .a PI softcopy workstation
environment. The particular application task demonstrated was the
recognition of significant changes of man-made objects in images of
the same location taken at different times. The goal of this
project is to develop a laboratory and a set of tools (as opposed to
building a complete system) which can be used to experiment with
developing aids for image analysts (not full automation). Future
work will involve adding 3-D models, using shadow information,
applying it to urban areas, and studying the use of specialized
image processing hardware. A set of viewgraphs is attached.
MITRE also has AI work going on at their Bedford, Massachusetts,
operation, and described four AI projects at STAT
MITRE/BEDFORD. The KNOBS project (which the AISG saw demonstrated
at Symbolics in Cambridge last Fall) provides assistance in tactical
air mission planning-. The KNOBS approach employs natural language
processing, rules, frames, and templates. The general architecture
has been reapplied to several other planning areas for NASA and the
Navy. MITRE has also been working in the field of Natural Language
(question-answering, inferencing, and command interpretation).
Their current interests are moving toward multiple ways of
presenting answers: using natural language and_:_g_aphics. Their
Knowledge-Based Automatic Programming project employs an application
knowledge base to facilitate rapid prototyping and debugging of a
system. This project is similar to RADC's work in this area but is,
perhaps, broader in scope. Next, described an Expert STAT
System they are building for NASA to support mission GO/NOGO
decisions by analyzing and validating sensor indications which
monitor the liquid oxygen supply. Finally, he talked about their
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Future Generation Computer Architecture project. This work involves
Multiple Instruction/Multiple Datastream machines and a "smart"
memory interconnect scheme to link multiple processors (up to,
perhaps, 1 million).
summarized several general research issues which the STAT
Bedford projects are attempting to address.
Developing a KNOBS Replanning System
- Resource allocation
- Monitoring missions
- Achieving interaction among missions
Disambiguating natural language text and maintaining a
conversational context
Achieving incremental program specifications changes,
removing temporary inconsistencies, and deciding which rule
to apply
Controlling mechanized reasoning for efficiency and for
naturalness
. Permitting continuous replanning
. Monitoring the results of a plan.
The last speaker was who presented a prototype STAT
expert system for resolving aircraft conflicts (a project for the
Federal Aviation Administration). The system, which was
demonstrated, uses information which predicts violations of safe
separation policies up to 30 minutes in advance. Twenty-seven
expert rules are then applied to determine for the air traffic
controller suggested strategies for resolving the forthcoming
conflict (e.g., plane,A ascend and plane B turn right). The rules
embody a set of doctrinal constraints about such things as
right-of-way, restricted air space, and general aviation
principles. A set of viewgraphs is attached.
Executive Secretary
AI Steering Group
STAT
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AI Briefing
10 May 1984
CAHIS Briefing Room
Wilson Building
MITRE C31/Washington
Expert Systems for Intelligence Fusion
and Situation Assessment
The battlefield environment is used as.a model to develop
expert systems to fuse and assess the dynamic information available.
Adaptation to the changing environment and automatic correction of
rules are being investigated. A demonstration will be presented.
Artificial Intelligence Applied to Military Planning
A demonstration Expert System has been developed which applies
rules to the logistic planning of crisis responses. Operating
bases and transportation facilities may be selected in this system.
A more powerful system is under development and will be discussed.
STAT
STAT
11:30 STAT
reinforce their strengths).
Human, Factors Design of Expert. Systems
The objective of this research is to develop a methodology to
assess the strength and weaknesses of human experts and to use this
information in the design of expert systems. A secondary objective
of this research is to develop methods to test the value added by
the system, (i.e., the degree to which the expert system does, in
fact, compensate or correct the weaknesses of human experts and
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The efforts discussed will include tactical planning, natural
language understanding and automatic programming.
AIRPAC - Advisor For Intelligent Resolution
of Predicted Aircraft Conflicts
An Expert System uses heuristic rules to develop and evaluate
a list of feasible actions to avoid aircraft conflicts. These
proposed solutions are presented to the air traffic controller for
selection. A demonstration will be presented.
Computer Vision as a Photographic Intelligence Aid
This talk will briefly describe MITRE's current effort to
adapt Computer Vision technology to aid the photo-interpreter, in
a softcopy workstation environment, to identify the first signs of
man-induced change of potential significance.
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STAT
STAT
STAT
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AN EXPERT SYSTEM FOR RESOLUTION OF AIRCRAFT CONFLICTS
COMPUTER DEMONSTRATION
MITRE/METREK
IR&D 95690
PROJECT TEAM:
CURTIS SHIVELY
KARL SCHWAMB
JILL NICOLA
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WHY CONSIDER KBS TECHNIQUES FOR ATC?
0 ATC REQUIRES COMPLEX DECISIONS, CURRENTLY PERFORMED BY HUMAN EXPERTS
0 L'IiMITATIONS;;)OF ALGORITHM-BASED COMPUTERIZED DECISION AIDS
- DIFFICULTY ESTABLISHING RELATIONSHIP TO HUMAN DECISION PROCESS
- DIFFICULTY EXPLAINING RATIONALE UNDERLYING OUTPUT DECISIONS
- SOME DIFFICULTY IN TESTING, CHANGING, MAINTAINING PROGRAM
0 KBS TECHNOLOGY ALLOWS EXPERT SYSTEM AUTOMATION.OF HUMAN DECISION
PROCESS
DATABASE OF ABSTRACT. DECISION RULES
- COMPUTER MAKES INFERENCES FROM INPUTS AND RULE BASE
- USER-FRIENDLY INTERFACE PROVIDES JUSTIFICATION FOR ANSWERS
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PURPOSE OF CONFLICT RESOLUTION EXPERT SYSTEM -
GIVEN:
0 PREDICTED CONFLICTS (POTENTIAL VIOLATIONS OF SAFE SEPARATION)
BETWEEN AIRCRAFT
PREDICTED 15-30 MINUTES IN ADVANCE FROM FLIGHT PLAN DATA
CHARACTERIZED BY GEOMETRY, AIRCRAFT ALTITUDE, SPEED, INTENT,
ETC.
PROVIDE:
0 RESOLUTION ALTERNATIVES IN ORDER OF PREFERENCE
- AIRCRAFT TO BE DEVIATED
- TYPE OF MANEUVER, INCLUDING PARAMETERS AND TIME OF EXECUTION
EXPLANATION OF RATIONALE UNDERLYING RECOMMENDATIONS
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CONSIDERATIONS PERTINENT TO RESOLVING CONFLICTS
Conflict Description
Conflict situation
Geometry--acosslsg,'`beadon. ovectfte. merging'
Altitude coals--btgb er low
Relative position (boils and wort). and velocity
Timeldistance to point of first violation
Neighboring aircraft
Aircraft-specific
Intent (at conflict and later)--accival, eta.
speed (general maneuverability)
Maneuver status (at conflict) turning. ate.
Type--)et. piston, turboprop
Category--OA. air cast/er, ate.
around speed
Metered? In queue[
Constraints on solution
Rnviconsental
Terrain
winds and severe weather
Bperial-use sic Paces
Traffic flows. including I(-M altitudes. etc.
Neighboring A/C
ATC costclctions--$VA, IQA. eta.
A/C-Bpecitic
service limits--maximum altitude
Performance limits--climb Cate, speed. etc.
Pilot ability to comply (aircraft weight. etc.)
A/C not subject to maneuvers
Interlocks on maneuvers vs. currant maneuver
Rules of the air
Goals of solution
Reduce number of conflicts
Don't preclude fallback solution it this one Calls
Preserve tight-of-way policy
Maneuver A/C not in arrival flow or metering queue
Minimise commands, no more vectors than one afloat at
dogleg '
Preserve long-tots intent--route bends. descent. etc.
Fuel efficiency
Preserve arrival ordering consistent with speed
ordering
minimize new delay consistent with metering goals
Try solutions in order of preference for given conflict
Rationale should be relatively transparent to controller
Provide lateral. long.. vent., or radar type separation
Insensitivity to wind and A/C performance data
uncertainty
Avoid risky solutions requiring controller monitoring
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ORGANIZATION OF CFR KNOWLEDGE
0 FACTS--DESCRIBE,CONFLICT SITUATION
EXPERT RULES--GENERATE LIST OF RESOLUTIONS IN ORDER OF PREFERENCE
0 CONSTRAINTS--REJECT OR REORDER POSSIBLE SOLUTIONS BASED ON OTHER FACTORS
- HIERARCHICAL ORDERING OF CONSTRAINTS
-- SHOWS RELATIVE IMPORTANCE OF CONSTRAINT VIOLATIONS
-- ALLOWS RELAXATION AND ACCEPTANCE OF MILD VIOLATIONS
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FORM OF RESOLUTION EXPERT RULES
0 GENERATE LIST OF RESOLUTIONS (AIRCRAFT AND MANEUVER) IN ORDER OF
PREFERENCE
0 INPUT FACTORS,
TYPE OF CONFLICT (CROSSING, HEADON, MERGING, OVERTAKE)
INTENT (ARRIVAL, DEPARTURE, OVERFLIGHT)
SPEED
TIME-TO-CROSSING (CROSSING CONFLICTS ONLY)
- TIME-TO-CONFLICT (CROSSING CONFLICTS ONLY)
- CLIMB RATE (DEPARTURE INTENT)
0 POSSIBLE MANEUVER CHOICES
ARRIVAL--SPEED REDUCTION, RESTRICTED DESCENT, VECTOR
q I
DEPARTURE--RESTRICTED CLIMB, VECTOR
OVERFLIGHT--SPEED REDUCTION, VECTOR, CLIMB/DESCEND TO NEW
ASSIGNED ALTITUDE
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FORM OF RESOLUTION EXPERT RULES
(CONCLUDED)
0 TOTAL OF 27 RULES
FOUR CONFLICT TYPES
SIX INTENT COMBINATIONS (ARRIVAL-DEPARTURE, ETC.)
FURTHER SUBDIVISION OF CROSSING OVF-OVF, MERGING OVF-OVF, AND
OVERTAKE ARV-ARV CASES
0 EXAMPLE EXPERT RULE
IF (CONFLICT-TYPE CROSSING -AC1 -AC2)
AND (INTENT DEPARTURE.-AC1)
AND (INTENT OVERFLIGHT -AC2)
THEN (FACT *POSS* ((RESTR-CLIMB -AC1)(VECTOR -AC1)
(VECTOR -AC2)(CHANGE-ALT -AC2)))
0 MANEUVER EXPANSION VIA SINGLE MAINTENANCE RULE
(VECTOR -AC) EXPANDS TO (RIGHT-TURN -AC)(LEFT-TURN -AC)
(CHANGE-ALT -AC) EXPANDS TO (CLIMB -AC)(DESCEND -AC)
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RATIONALE FOR CURRENT SET OF CONFLICT RESOLUTION EXPERT RULES
0 CROSSING CONFLICT (AIRCRAFT IS PRIMARY FACTOR)
AIRCRAFT--PREFERENCE BASED ON INTENT, IF SAME, MANEUVER THE
ONE FARTHER AWAY (ARV, OVF) OR SLOWER CLIMBER (DEP)
- MANEUVER--PREFER ALTITUDE CHANGE OR'RESTRICTION TO ACHIEVE
CLEAR VERTICAL SEPARATION UNTIL AFTER HORIZONTAL
;::,`.CROSSING, EXCEPT PREFER SPEED REDUCTION, IF OVF-OVF
AND TIME-TO-CONFLICT GREATER THAN 20 MINUTES
0 HEADON CONFLICT (MANEUVER IS PRIMARY FACTOR)
- MANEUVER--PREFER VECTOR TO GAIN CLEAR-LATERAL SEPARATION
- AIRCRAFT--PREFERENCE BASED ON INTENT, IF SAME. MANEUVER
FASTER A/C
0 MERGING CONFLICT (AIRCRAFT IS PRIMARY FACTOR)
- AIRCRAFT--PREFER SLOWER ONE TO ACHIEVE NECESSARY SPEED
ORDERING
- MANEUVER--PREFER VECTOR TO MERGE SLOWER IN BEHIND FASTER
AIRCRAFT
-;..,EXCEPTION--IF OVF-OVF AND TIME-TO-CONFLICT GREATER THAN 20
MINUTES PREFER SPEED REDUCTION FOR FASTER A/C
0 OVERTAKE CONFLICT (AIRCRAFT IS PRIMARY FACTOR)
- AIRCRAFT--PREFERENCE BASED ON INTENT. IF SAME, MANEUVER
FASTER AIRCRAFT
- MANEUVER--PREFER VECTOR FOR CLEAR LATERAL SEPARATION, EXCEPT
PREFER SPEED REDUCTION, IF SMALL SPEED DIFFERENCE (ARV, ARV)
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CONSTRAINT RULES CURRENTLY USED IN CFR EXPERT SYSTEM
0 HIERARCHICAL ORDERING
SEVERE (FOUR RULES)
-- DON'T CLIMB/DESCEND IF SOMETHING ABOVE/BELOW
-- DON'T LEVEL OFF IF DEPARTURE/ARRIVAL AND SOMETHING
BELOW/ABOVE
MODERATE (FIVE RULES)
-- AVOID TURNING RIGHT/LEFT IF SOMETHING TO RIGHT/LEFT
-- AVOID CLIMBING AIRCRAFT IF WITHIN 3,000 FEET OF
SERVICE CEILING
-- AVOID TURNING RIGHT/LEFT IF TIME-TO-CONFLICT LESS THAN
7 MINUTES
- MILD (FOUR RULES)
-- UNDESIRABLE TO MANEUVER AIRCRAFT IN METERING QUEUE
-- UNDESIRABLE TO TURN RIGHT/LEFT IF ROUTE BENDS
LEFT/RIGHT
-- UNDESIRABLE TO CLIMB IF INTENT CHANGE OVERFLIGHT TO
ARRIVAL
0 REORDERING OF SOLUTIONS
- NO VIOLATIONS, ONLY MILD, AT MOST MODERATE, SOME SEVERE
- ORIGINAL PREFERENCE ORDER IS PRESERVED AMONG SOLUTIONS WITH
GREATEST VIOLATION IN SAME CATEGORY
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CAPABILITIES OF CURRENT SOFTWARE IMPLEMENTED ON
COMMAND AND MANAGEMENT INFORMATION SYSTEMS (CAMIS) LAB-
0 EXPERT SYSTEM FOR RESOLVING CONFLICTS
APPLIES RULES TO FACTS DESCRIBING A TWO-AIRCRAFT CONFLICT
SCENARIO
RECOMMENDS SOLUTION ALTERNATIVES IN ORDER OF PREFERENCE
0 EXPLANATION OF RESULTS
- WHICH RULES WERE ACTIVATED
- HOW GIVEN FACTS LED TO INDICATED SOLUTION
0 GRAPHICAL PRESENTATION OF CONFLICT SCENARIOS
- ROUTE AND ALTITUDE PROFILES ON RAMTEK COLOR GRAPHICS DISPLAY
0 RULE BASE DEVELOPMENT AIDS
DEPICT RULE INTERACTIONS DUE TO COMMON INPUT AND OUTPUT
CLAUSES
- ALLOW RULE EDITING DIRECTLY IN LISP ENVIRONMENT
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PHOTO INTELLIGENCE PROBLEM
TOO MUCH IMAGERY
? TOO FEW TRAINED PHOTO INTERPRETERS AND INTELLIGENCE ANALYSTS
? COMPUTER VISION IS GOOD, HOW CAN IT BE USED:
? IN THE SOFTCOPY WORKSTATION ENVIRONMENT
TO INCREASE PRODUCTIVITY RATHER THAN DISTRACT THE VIEWER
? PROBLEM DOMAIN
?
FY84:
DETECT NEW MAN-MADE STRUCTURES IN THE WILDERNESS
?
FY85:
CONSTRUCT BLUEPRINTS/MAPS/MODELS OF NEW
BUILDINGS/TOWERS/SHIPS
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SOLUTION
IN FY84 WE EXPECT TO HAVE A SET'OF GENERAL PURPOSE
COMPUTER VISION SOFTWARE TOOLS THAT CAN BE USED TO
DETECT NEW MAN-MADE STRUCTURES IN THE WILDERNESS
FROM PAIRS OF DIGITIZED AERIAL PHOTOS.
IN FY85 WE PLAN TO USE MANY OF-THESE TOOLS TO COMPARE
NEW IMAGERY WITH SYNTHETIC IMAGERY PREDICTED FROM A
3-DIMENSIONAL SCENE MODEL, FURTHERMORE, WE PLAN TO
USE THE CHANGES WHICH ARE DETECTED TO UPDATE THE
SCENE MODEL,
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IMAGE PROCESSING TECHNOLOGIES
IMAGE ENHANCEMENT
(IMAGE IN - BETTER IMAGE OUT)
USED TODAY
---------------------------------------------------------------------------------
NOT USED TODAY
IMAGE PROCESSING - PATTERN RECOGNITION
(FEATURE EXTRACTION)
COMPUTER VISION
ASSIMILATION, MATCHING OF FEATURES
TOWARD OBJECT RECOGNITION
ARTIFICIAL INTELLIGENCE
SCENE INTERPRETATION
I RELATIONSHIPS BETWEEN OBJECTS IN A SCENE
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TECHNICAL CHALLENGES OF IMAGERY DATA
? DIFFERENCES DUE TO VIEWING GEOMETRY
ALTITUDE
? VIEWING ANGLE
? LAND TOPOGRAPHY
? DIFFERENCES DUE TO LIGHTING,EFFECTS
? SUN ANGLE
? SHADOWS
? GLARE
BACK SCATTERED LIGHTING
? DIFFERENCES DUE TO OCCLUSION
? BUILDING - BUILDING
? BUILDING - GROUND
? CLOUD COVER
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FY84 APPROACH
NEW
DIGITIZED
IMAGE
SOBEL
EDGE
OPERATOR
MARYLAND
EDGE
THINNER
HOUGH
LINE
FITTER
GENERATOR
PARAMETERS
- GAIN
- DECISION
- CONTROL
SOBEL
EDGE
OPERATOR
MARYLAND
EDGE
THINNER
ILLINOIS HOUGH
GRAPH LINE oj~ MATCHER FITTER
COLOR
TINT
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ADAPTIVE TRAINING
EACH TOOL HAS SEVERAL GAIN/DECISION/CONTROL PARAMETERS
? DIFFI`CULT TO TUNE BY HAND FOR A GIVEN CLASS OF IMAGERY
REQUIREMENTS
? GROUND TRUTH
? ERROR ANALYSIS PROGRAM
? OPTIMIZER
OPTIMIZER
Error
Parameters
Data
TOOL
Ground Truth
ERROR
ANALYSIS
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FY85 APPROACH
NEW
IMAGERY
EDGE
DETECTOR
EDGE
THINNER
DISPLAY
OF 3-D
MODELS
COLOR
TINTER
MATCHER
- FY84 SOFTWARE
- FY85 SOFTWARE
- DATA
EDGE
SHADOW
PREDICTOR
NEW EDGES RECONSTRUCTED
OLD IMAGERY
INTERACTIVE
INPUT
EDGE
CONSTRAINT
ENFORCEMENT
OLD 3-D
MODEL
OLD MODEL
MODEL E
EDITOR
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NEW MODEL
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FY84 TECHNOLOGY
? EDGE OPERATOR
? LOW SENSITIVITY TO LIGHTING/VIEWING ANGLE
? FACTOR OF 10 DATA REDUCTION
? FAILS;TO DETECT 5% OF ACTUAL "GOOD" EDGES
? DETECTS "EXTRA" EDGES
? EDGE THINNER
? REMOVES 90% OF "EXTRA" EDGES PRODUCED BY THE EDGE DETECTOR
? FACTOR OF 3 DATA REDUCTION
? REMOVES 5% OF THE "GOOD" EDGES
? LINE FITTER
? SEPARATES MAN-MADE OBJECT EDGES FROM NATURAL EDGES
? RESYNTHESIZES SOME OF THE LOST "GOOD" EDGES
? FACTOR OF 5 DATA REDUCTION
? SNOW/CLOUD COVER DOES NOT PRODUCE STRAIGHT LINES
? GRAPH MATCHER
? DETECTS DIFFERENCES (IN THE STRAIGHT LINES PRODUCED FROM
MAN-MADE OBJECTS)
? LOW SENSITIVITY TO EXTRA/LOST EDGES
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ADDITIONAL TECHNOLOGY
? DISPLAY OF 3-D MODELS WITH HIDDEN. SURFACE REMOVAL
? SOFTWARE (MODIFIED MOVIE BYU)
? INPUT:. 3-D MODEL OUTPUT: IMAGE
? EDGE/SHADOW PREDICTOR
? ALGORITHMS EXIST (MUST BE PROGRAMMED)
? INPUT: 3-D MODEL OUTP-UT: EDGES
? EDGE CONSTRAINT ENFORCEMENT
? ALGORITHMS EXIST (MODIFIED STRAIGHT LINE FITTER)
? INPUT: EDGES OUTPUT: STRAIGHT/CURVED LINES
? FITS EDGES TO LINES AND CURVES
? MAKES EDGES PARALLEL, VERTICAL, EQUAL LENGTH, ETC.
? MODEL EDITOR
? PARTIAL SOFTWARE (MODIFIED GRAPH EDITOR)
? INPUT: INTERACTIVE + STRAIGHT/CURVED LINES + MODEL
? OUTPUT: NEW MODEL
? CONSTRUCT SIMPLE SOLID MODELS FROM PARALLEL EDGES
? CAN COMBINE TWO SOLID MODELS TO FORM A NEW SOLID MODEL
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EXPECTED RESULTS
? FACTOR OF 10 INCREASE-IN PHOTO INTERPRETER-TASK-
THROUGHPUT
? A MITRE DEMONSTRATION SYSTEM THAT USES COMPUTER
VISION TOOLS TO ASSIST AN INTELLIGENCE ANALYST
TO INTERACTIVELY UPDATE A 3-DIMENSIONAL MODEL
FROM NEW IMAGERY
? SYNTHESIS OF IMAGERY FROM OBLIQUE ANGLES NOT
AVAILABLE TO THE.SENSOR
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GRADIENT BASED EDGE DETECTORS
? ESTIMATE THE GRADIENT OF THE IMAGE FUNCTION USING DISCRETE
SPACIAL CONVOLUTION
? HYPOTHESIZE THAT EDGES PASS THROUGH POINTS WHERE THE MAGNITUDE
OF THE GRADIENT VECTOR Q a,b IS LARGER THAN A THRESHOLD t.
? SOBEL
T
- 1=-n 1=-n
U = a
? PARAMETERS
r, a, t
2 0
1 0
Vi,1 P (a-i), (b-1)
1 2 1
0 0 0
-1 -2 -1
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Ui,J P (a-i ), (b'=1)
T I
i=-n 1=-n
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HOUGH TRANSFORM AND STRAIGHT LINE FITTING
? PARTITION SPACE INTO n by n CELLS
? HOUGH TRANSFORM x, y r, 8 r = x? cos9 + Y. sing
? ACCUMULATOR ARRAY
? THRESHOLD t
? PARAMETERS n, t, L~ 8
Straight
Line
r Detected
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
FEATURE GRAPH MATCHING
Input >
Feature
Graphs
PROTOTYPE FORMATION
DISTANCE RECALCULATION
NORMALIZATION
CONSTRAINT ENFORCEMENT
OUTPUT PRUNING
Relaxation
Loop
Output
Matched/Unmatched
Features
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
HUMAN FACTORS DESIGN OF EXPERT SYSTEMS
IR&D UPDATE
Frank Stech
Joseph Schmu l l e r
The MITRE Corporation 10 May 1984
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
HUMAN FACTORS DESIGN OF EXPERT SYSTEMS
? Issue: Expert Systems (ES) are designed to capture,
reproduce.. and distribute human expertise repackaged
as computer programs.
? Problems:
How can the ES designer capture human expertise
accurately, completely, and efficiently?
How can the ES designer assess components of
human expert i?se to improve subobt ima l components?
How can the ES designer reassemble the human and
enhanced components to represent expertise
precisely?
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
TECHNIQUES AND TOOLS
? Expert Modeling Methods: (Applicable to I R&D)
Expert-Novice Comparisons
Expert Protocol Analysis
Information Processing
Experiments
Simulations
Field Observations
Developmental. Studies
Cross-cultural Comparisons
Historical Comparisons
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
TECHNIQUES AND_ TOOLS (CONCLUDED)
? Tools
Chronometric measures (e. g., reaction time,
p rocess i ng;,,k.t ime, chunking)
Multidimensional categorization analysis (e. g,
scaling, clustering)
Subjective probability analysis (e.g.,
Non-Bayes i a n probability revision)
Problem-solving (e.g., accuracy, sequences,
relationships)
Multiple regression (e.g.,, input-output trace,
information integration modeling)
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PROTOTYPE ASSESSMENT: TACTICAL MAP BATTLEFIELD READING
? Methodology: Chunking (Chess Experts) applied to
tactical maps
Copying maps
Reconstructing maps from memory
Estimating classes and overall situation
? Stimuli
Meaningful, semi-meaningful, and anomalous
tactical maps
Varied map symbology; e.g., unit symbols, unit
designation, unconventional symbols, chess
symbols
? Data: I me rp l acement times, glances, gaze, symbol
placement order, protocol Is
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Battlemap
Appears on
Screen for 2 min.
Subject
Studies _.-._---
Battlemap
Battlemap
Disappears
'Copy Map' &
Palette of Features
Appear
Subject Reconstructs
as much of Battlemap
as he can, using
Copy-Map, Palette
and Light-Pen
Subject presses
a key, Copy-Map
and Palette disappears,
original Battlemap
reappears, for a
maximum of one
minute
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SQ
FQ
S & F 0
V
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I I I I I
Elements Correctly Recalled vs. Trials -- F Q
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Elements Correctly K-suilea vs. Trials -- F a S Q
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Types of Elements Correctly Recalled vs. Trials -- -0
Types of Elements Correctly Recalled vs. Trials -- F & S Q
a
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a
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^
19
11
El
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
PILOT STUDIES
? Study 1: Map Reading
Attention affects chunking
Chunks reflect pattern recogfn i t i on
- Memory/Learning curves
? Study 2: Map Assessment
Chunks relate to categories
Categories relate to summaries
Summaries relate to assessments
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
PILOT STUDIES (CONCLUDED)
? Study 3: Summary Composition
- Report chunking
- Cova riat ion assessment
- Availability effects
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
EXPERIMENTAL SERIES-
Tactical battlemap reading: What are the basic
elements and relationships?
? Tactical battlemap assessment: What is the transfer
function from-symbolic map input to verbal/textual
assessment output?
? Tactical summaries composition: Now are tactical
reports transformed and integrated into tactical
assessments and summaries?
? Map and report integration and assessment: How are
tactical reports integrated with ba tt l emap data and
transformed into situation assessments?
? D namic assessment: How does chang inj information
(reports and maps impact on analyst s assessments?
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
. ANALYST
A Knowledge-Based
Intelligence Support System
JTF Demonstration
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
What Is ANALYST?
ANALYST is an Intelligence Support System. . .
? Targeted for Army Corps and Allied Tactical Operations Centers (Air Force)
? Supports All Source Sensor Fusion and Primary Information Request Processing
? Is Capable of Dynamic Refinement of Findings from New Data
... Composed of Integrated Expert .System Techniques
? Both Data Driven and Request Driven
? Uses Both Hierarchical and Spatial Data Structures
? Employs Procedural, Propositional, and Iconic (Image) Knowledge Structures
? Maintains Truth Justifications
? Includes Knowledge-Engineering Tools
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Data
Bases
Expert Systems
Triggers
Updates
Control
Mechanism
Knowledge
Bases
? Use a Knowledge-Base of -Rules-of-Thumb Provided by
Experts
? Capture Fundamental Principles of the Problem Domain
as Well as General Methodology
? Solve Complex Problems Well
? Can Interact Intelligently with the User
? Are Useful for Interpretation, Diagnosing, Predicting,
Analyzing, Consulting
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
KVM
Knowledge
Engineering
PIRIIR
Handler
ANALYST Architecture
Questions
Truth
Maintenance
Answers/Critical Information Gaps
Sensor
Fusion
Module
Intelligence
Reports
Sensor
Control
Tasking
Battlefield Environment Model (BEM)
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Commander
G2
.,Terminal
SITMAP
Display
'Collection
Management
. Terminal ,
Scenario
Controller
Terminal
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Sensor Coverage Symbology
Moving Target
Indicator (MTI)
COMINT
ELINT
Counter Mortar/
Counter Battery
(CMCB)
IMINT
(Photo)
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
MITRE
Threat Modeling
? Experimental Boundaries
- Soviet/WP Division from SCORES
- Company/Battery Resolution
- Stylized Terrain
? Emphasis on Activities
- Movement
- Emissions
? Behavior Modeling
- Object-Oriented Programming
- Activities are Rule-Based
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
MITRE
Sensor Modeling
? Current Experimental Boundaries
- Corps/Division Orientation
- Continuous Resource Availability
Optimal Communications
- No Formal Models
? Emphasis on Geographic Coverage
- Platform Flight Paths, Time-on-Station
- Ranges, Coverage Angles
? Interactive Tasking -- Sensor Control Station
- View "TAKE"
- Reposition Sensors
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Level 3 (?)
Level 2 (FY84)
Level 1 (FY83)
Level 0 (FY83)
Threat
Units &
Hierarchies
Levels of
ANALYST Reasoning
Activity
Groups
SSensor Reports Establish Activity
Groups
- _ - - -~~ ~ Analyze \% 1 `I
Threat l4.40.1
1 ~ t Intentions
Analyze Logical
Critical )4-10) Indicator
Indicators J Network
Merge Rules
Refinement Rules
Templates
Purge Rules
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MITRE
Level 3 (?)
Level 2 (FY84)
Level 1 (FY83)
Level 0 (FY83)
Levels of
ANALYST Reasoning
Analyze t t 1t
I ~---t Threat IMI
Intentions I I
Threat
Units &
Hierarchies
Analyze Logical
Critical H Indicator
Indicators Network
Hypothesize Single
r
e M
R
Sensor
Reports
Establish
Activity
Groups
t ou
c
erge
u es
Pattern Refinement Rules
Rules Templates
Purge Rules
Single
Source
Cluster
Rules
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
Results
With 35% coverage
? ANALYST locates over 70% of the active enemy
battalions
? Accuracies average 750 meters circular error probable
(CEP)
? General force movement trends are detectable
? System tracked individual movement of 15% of the
regimental and battalion command posts
With 20% coverage
? Over 50% of the active battalions located
? General force movement trends still discernible
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
MITRE
ANALYST System Characteristics
Capabilities
? Knowledge-Based .
- Can View On-Going Analytical Processes
- Can Edit Rule-Base On-Line
- Straightforward Architecture
- Keys on Patterns of Activity
? Processing
- Stays Abreast of. Battlefield Dynamics,,,-,
- Real-Time Speed
- Multiple-Source
- Does Not Require a Mainframe Environment
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 Approved For Release 2008/08/22 : CIA-RDP86M00886R000500050006-9
MITRE
ANALYST System Characteristics
Limitations
? Idiot-Savante Nature
- Totally Dependent on "Expert" Rules
- Does Not Introspect
? Single Scenario Development
? Needs Operational Knowledge Instead of
Demonstration Knowledge
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