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Command and Control Modeling for Synthetic Battlespaces: Flexible Group Behavior. Randall W. Hill, Jr. Jonathan Gratch USC Information Sciences Institute ASTT Interim Progress Review May 24, 1999. Agenda. Synthetic Forces Problem Program Hypotheses Technologies and R&D

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Command and control modeling for synthetic battlespaces flexible group behavior l.jpg

Command and Control Modeling for Synthetic Battlespaces:Flexible Group Behavior

Randall W. Hill, Jr.

Jonathan Gratch

USC Information Sciences Institute

ASTT Interim Progress Review

May 24, 1999


Agenda l.jpg

Agenda

  • Synthetic Forces Problem

  • Program Hypotheses

  • Technologies and R&D

  • Significant Results & Expected Results

  • Technology Transition Products & Efforts

  • Problem Areas

  • Programmatic Issues


Synthetic forces problem l.jpg

Synthetic Forces Problem


Problem l.jpg

Problem

  • Need cost-effective C2 modeling

    • Replace / augment human controllers with automated C2

    • Represent a wide range of organizations and situations

  • Need realistic C2 behavior

    • C2 models must make believable decisions

    • The outcomes of C2 operations need to be credible


Project goals l.jpg

Project Goals

  • Develop autonomous command forces

    • Act autonomously for days at a time

      • Reduce load on human operators

    • Behave in human-like manner

      • Produce realistic training environment

    • Perform C3I functions

      • Reduce the number of human operators

      • Create realistic organizational interactions


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Program Hypotheses


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Hypotheses

  • Flexible behavior requires the ability to handle situation interrupts

  • Flexible group behavior requires:

    • Understanding behavior of groups of entities

    • Planning a mission for groups against groups

    • Executing a mission in a coordinated manner


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Hypotheses

  • Flexible group behavior interleaves the processes of situation assessment, planning, execution, and plan repair

  • Coordinated group behavior requires a theory of multi-agent interaction


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Technologies and R&D


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Technologies

  • Continuous Planning

    • Depends on understanding evolving situations

    • Implements planning as a dynamic process

    • Achieve goals despite unplanned events

  • Collaborative Planning

    • Coordinate group behavior

    • Requires understanding behavior of other groups

    • Reason about organizational constraints


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Technologies

  • Situation Awareness

    • Current situation

      • Need a consolidated picture

      • Requires situation assessment at multiple echelons

    • Future situation

      • Integrate planning with future sensing requirements

      • Formulate Priority Intelligence Requirements (PIR)


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Mission Capabilities

  • Army Aviation Deep Attack

    • Battalion command agent

    • Company command agents

    • CSS command agent

    • AH64 Apache Rotary Wing Aircraft

    • Suppression of Enemy Air Defense (SEAD) by indirect fire (partially implemented)

    • Intelligence assets (partially implemented)


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Battalion Deep Attack

MLRS

SLAR

SEAD

HA

BP

HA

CSS

FLOT

FARP


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C2 Architecture

Situation Report

(understanding)

Situation Report

(understanding)

Battalion

Commander

Operations Order

(plan)

….

Operations Order

(plan)

Operations Order

(plan)

Company A

Commander

Company X

Commander

Situation Report

(understanding)

Company A

Company X

….

Pilot

Pilot

Pilot

Pilot

Pilot

Pilot

Helicopter

Helicopter

Helicopter

Helicopter

Helicopter

Helicopter

Actions

ModSAF

Actions

Percepts

Percepts


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Architecture

  • Planner

    • Implements continuous planning capabilities

  • Plan manager

    • Augments collaborative planning with organizational reasoning and Military Decision Making Process

  • Time Manager

    • Manages temporal constraints

  • Domain Theory

    • Maintains plan management and tactical knowledge

  • Situation Assessment

    • Fuses sensors, reports, and expectations

    • Generates and updates current world view


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C2 Entity Architecture

Plan

Manager

Management

Theory

(domain independent)

Management

Plans

Tactical Plans

Planner

(General Purpose

Reasoner)

Tactical

Domain Theory

World Model

Facts, inferences

Expectations

Situation Assessment

Situation Reports, Sensing

OPORDER

Other Communications

Synthetic Battlespace


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Technologies and R&D:Continuous Planning


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Continuous Planning

  • Plan generation

    • Sketch basic structure via decomposition

    • Fill in details with causal-link planning

  • Plan execution

    • Explicitly initiate and terminate tasks

    • Initiate tasks whose preconditions unify with the current world

    • Terminate tasks whose effects unify with the current world

  • Plan Repair

    • Recognize situation interrupt

    • Repair plan by adding, retracting tasks


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What are Plans?

  • Hierarchically ordered sequences of tasks

  • Plans capture assumptions

    • Column movement assumes enemy contact unlikely

  • Plans capture task dependencies

    • Move_to_Holding_Area results in unit being at the HA, (precondition to moving to the Battle_Position)

    • OPFOR and Co must be at the Engage_area simultaneously


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Plan Generation Example

World Model

Attack(A, Enemy)

at(A,FARP)

at(Enemy,EA)

Destroyed(Enemy)

Destroyed(Enemy)

. . .

Engage(A,Enemy)

Move(A,BP)

at(A,FARP)

at(A,BP)

at(A,BP)

Destroyed(Enemy)

init

at(Enemy,EA)


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Battalion Tactical Plans

Co

Deep Attack

Co

Deep Attack

Move

Move

Engage

Return

Move

Move

Engage

Return

FARP

Operations

Company B plan

CSS

plan

Move

Move

Move

Move

Move

Company A plan

Move

Move

OPFOR Plan


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Situation Interrupts Happen!

Current World

Attack(A, Enemy)

at(A,FARP)

at(Enemy,EA)

destroyed(Enemy)

destroyed(Enemy)

active(A)

Engage(A,Enemy)

Move(A,BP)

at(A,FARP)

at(A,BP)

at(A,BP)

destroyed(Enemy)

Start of OP

active(A)

active(A)

ADA

Attack


Reacting to situation interrupt l.jpg

Reacting to Situation Interrupt

  • Situations evolve unexpectedly

    • Goals change, actions fail, intelligence incorrect

  • Determine whether plan affected

    • Invalidate assumptions?

    • Violate dependency constraints?

  • Repair plan as needed

    • Retract tasks invalidated by change

    • Add new tasks

    • Re-compute dependencies


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Technologies and R&D:Collaborative Planning


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Collaborative Planning

  • Represent plans of others

    • Extend plan network to include others’ plans

  • Detect interactions among plans

    • Same as with “normal” plan monitoring

  • Apply planning modulators:

    • Organizational roles

    • What others need to know

    • Phase of the planning

    • Stance of the planner wrt phase and role


Plan interaction example l.jpg

Plan Interaction Example

Move(A,BP)

Engage(A,Y)

at(A,BP)

at(A,BP)

at(A,FAA)

Dead(Y)

at(gas,FAA)

Attack Helicopter Company Plan

Operation Begins

Move(CSS,HQ)

at(gas,HQ)

at(gas,FAA)

at(CSS,HQ)

resupplied(HQ)

at(CSS,FAA)

Combat Service Support Plan


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Planning Stances

  • Authoritative

    • Order subordinate to alter his plans

  • Deferential

    • Change my plans to de-conflict with superior

  • Helpful

    • Help peer to resolve conflicts in plan

  • Self-serving

  • Adversarial

    • Try to introduce conflict in other agent’s plan


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Elaboration: Being Helpful

  • Planning issues

    • Propose doing activities that facilitate others’ plans

    • Avoid introducing threats into others’ plans

  • Communication Issues

    • Collaboration protocols: propose, accept, counter

    • Relevance reasoning

      • Which of my tasks would others want to know

        • e.g. “Honey, I’m going to the market”


Elaboration self serving l.jpg

Elaboration: Self-serving

  • Planning issues

    • Notice things that others might do for me

    • Ignore threats I introduce into other’s plans

      Unless that keeps them from doing things for me

  • Communication Issues

    • Deception

      • e.g. Someone might not help me if the knew what I was really planning


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Plan Management

  • Must model when to use different stances

    • Involves organizational issues

      Where do I fit in the organization

    • Stances may need to change over time

      During COA Analysis, adopt an adversarial stance towards ones own plans

  • Must model how stances influence planning

    • How do we alter COA generation


C2 entity architecture31 l.jpg

C2 Entity Architecture

Plan

Manager

Management

Theory

(domain independent)

Management

Plans

Tactical Plans

Planner

(General Purpose

Reasoner)

Tactical

Domain Theory

World Model

Facts, inferences

Expectations

Situation Assessment

Situation Reports, Sensing

OPORDER

Other Communications

Synthetic Battlespace


When to use a stance l.jpg

When to Use a Stance

  • Model the collaborative planning process

    • Includes management tasks that modulate the generation of tactical plans

      • Tasks refer to specific tactical plans

      • Specify preconditions on changing stance

    • Includes knowledge of one’s organizational role

  • Planner constructs management plans

    • Use same mechanisms as tactical planning


Management plan example l.jpg

Management Plan Example

  • Explicitly model the Military Decision Making Process

Tasks

Stances

COA

Development

Authoritative towards subordinates

Deferential towards superiors

Adversarial towards OPFOR

COA

Analysis

Authoritative towards OPFOR

Adversarial towards self (war gaming)


Implementing stances l.jpg

Implementing Stances

  • Implemented as search control on planner

    • Plan manager

      Takes executing management tasks

      Generates search control recommendations

  • Example: Deferential Stance

    • When giving orders to subordinates

      Indicate subset of plan is fixed (defer to this)

      Indicate rest of plan is flexible

    • Plan manager enforces these restrictions


Interaction example l.jpg

Interaction Example

Deferential towards

Make CSS Planner defer to Company A’s Plan

Move(A,BP)

at(A,BP)

at(A,FAA)

at(gas,FAA)

Manager

Retract

Initial State

Move(CSS,HQ)

Retract

Planner

at(gas,HQ)

at(gas,FAA)

at(CSS,HQ)

at(CSS,FAA)

Combat Service Support Plan


C2 entity architecture36 l.jpg

C2 Entity Architecture

Plan

Manager

Management

Theory

(domain independent)

Management

Plans

Tactical Plans

Planner

(General Purpose

Reasoner)

Tactical

Domain Theory

World Model

Facts, inferences

Expectations

Situation Assessment

Situation Reports, Sensing

OPORDER

Other Communications

Synthetic Battlespace


Technologies and r d situation awareness l.jpg

Technologies and R&D:Situation Awareness


Situation awareness l.jpg

Situation Awareness

  • Planner needs a consolidated picture of the current situation in the battlespace

    • Determines which goals and tasks are achievable

    • Influences the choice of strategies and actions

    • Allows the detection of imminent plan failure

    • Enables re-planning

  • Situation assessment produces a current World Model

    • Monitor plans with respect to world model

    • Situation awareness = world model + plans/tasks


Situation assessment l.jpg

Situation Assessment

  • Performed at multiple echelons

    • Scouts performing reconnaissance of battlespace

    • C2 staff assimilates scouting and sensor reports

  • General process:

    • Identify entities

    • Classify groups of entities as units

    • Determine units’ functionality, capabilities, plans, intent

  • Technical Issues

    • Pilot awareness and information overload

    • Situation assessment techniques


Pilot situation awareness l.jpg

Pilot Situation Awareness

  • Synthetic worlds are information rich

    • 100’s of other entities

    • Vehicle instruments

    • Terrain, weather, buildings, etc.

    • Communications (messages)

    • Amount of information will continue to increase ….

  • Perceive, understand, decide and act

    • Comprehend dynamic, complex situations

    • Decide what to do next

    • Do it!


Information overload l.jpg

Information Overload


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Roots of the Problem

  • Naïve vision model

    • Entity-level resolution only

    • Unrealistic field of view (360o, 7 km radius)

  • Perceptual-Cognitive imbalance

    • Too much perceptual processing

    • Cognitive system needs inputs, but …

    • It also needs time to respond to world events


Approach l.jpg

Approach

  • Create a focus of attention

    • Apply attention mechanisms to entity perception initially

    • Incorporate filters

    • Implement a zoom lens model (covert attention)

  • Stages of perceptual processing

    • Attention in different stages: preattentive & attentive

  • Control the focus of attention

    • Goal-driven

    • Stimulus-driven


Zoom lens model of attention eriksen yeh 1985 l.jpg

Zoom Lens Model of Attention(Eriksen & Yeh, 1985)

  • Attention limited in scope

    • Multi-resolution focus

    • Magnification inversely proportional to field of view

  • Low resolution

    • Large region, encompassing more objects, fewer details

    • Perceive groups of entities as a coherent whole

  • High resolution

    • Small region, fewer objects, more details

    • Perceive individual entities (e.g., tank, truck, soldier)


Low resolution l.jpg

Low Resolution


Perceptual grouping l.jpg

K

K

K

Perceptual Grouping

  • Preattentive

  • Gestalt grouping

    • Involuntary

    • Proximity-based

    • Other features

  • Dynamic

  • Voluntary grouping


Group features l.jpg

Group Features

  • Quantity and composition

  • Activity

    • Moving

    • Shooting

  • Location

    • Center-of-mass

    • Bounding-box

  • Geometric relationships wrt pilot

    • Slant-range, azimuth, etc.


High resolution l.jpg

High Resolution


Entity features l.jpg

Location (GCS)

Speed

Velocity

Orientation

Slant Range

Force

Object, Object Type

Vehicle Class

Function

Sense Name

Altitude

Angle Off

Target Aspect

Magnetic bearing

Heading

Status

Lateral Range

Lateral Separation

Closing Velocity

Vertical Separation

Entity Features


Control of attention l.jpg

Control of Attention

  • Goal-driven control

    • Agent controls the focus / resolution of attention

      • Low resolution: Scouting groups of enemy; escorting group

      • High resolution: Search for air-defense entities; engage target

    • Sets filters that select entities for WM

  • Stimulus-driven control

    • Attention can be captured involuntarily by a visual event

      • Muzzle flash (luminance contrast, abrupt onset)

      • Sudden motion (abrupt onset)


Goal driven attention l.jpg

Overwatch

Position

Land

Sea

Overwatch

Position

Transport Carrier

Rendezvous

Point

Escort Carrier

Goal-driven Attention

  • Escort task

  • Orient on group

  • Voluntary grouping


Stimulus driven attention l.jpg

High Resolution

Low Resolution

Stimulus-driven Attention


Situation awareness at higher echelons l.jpg

Situation Awareness at Higher Echelons

Command Entity

Situation Reports

Command Entity

Command Entity

Situation Reports

Situation Reports


Situation assessment54 l.jpg

Situation Assessment

  • Identify entities

    • Fuse scouting reports

  • Classify groups of entities as units

    • Cluster entities into unit-sized groups

    • Classify units into functional types

  • Determine capabilities, plans, intent


Clustering and classification l.jpg

Clustering and Classification

  • Bottom-up and top-down approach

  • Bottom-up clustering based on proximity

    • Identify a group of entities close to each other

    • Other useful features: color, orientation, speed

  • Top-down classification based on doctrine

    • Threat templates

    • Issues: which template, partial matching


Bottom up clustering l.jpg

Bottom-up Clustering

  • Hierarchical Clustering

    • Partitioning starting at the top until a satisfactory level (e.g. individual units)

  • Robust Clustering

    • Nearest-neighbor using center of mass

      • Works well for hierarchical clustering

      • Requires a parameter of minimal distance

    • Density-based clustering

      • Works well on different shapes of patterns

      • No parameter is required (or can be learned)


Top down classification l.jpg

Top-Down Classification

  • Classification and prediction

    • Classification based on threat templates

      • Doctrine of situations, actions, formation and capacities

      • Matching clustered units with templates for classification

    • Partial matching to predict the location of missing units

  • Encoding threat templates

    • Encoding spatial information for symbolic processing

      • kD-tree to encode spatial relationships

    • Adding possible actions to nodes (units)


Future situation awareness l.jpg

Future Situation Awareness

  • Model how tactical intelligence influences planning

  • Future situation: knowledge goals

    • What will I need to know for this plan to work?

    • Establish Priority Intelligence Requirements (PIR)

      • What commander needs to know about opposing force

    • Drives the placement of sensors and observation posts

    • Constrains the pace of plan execution

  • Rarely addressed in current C2 models


Intelligence critical for realistic c 2 l.jpg

Intelligence Critical for Realistic C2

  • Close interplay between intelligence and COA Development

    • Intelligence guides COA development

    • COA development drives intelligence needs

    • Intelligence availability constrains actions

      • Some COA must be abandoned if one can’t gather adequate intelligence


Intelligence critical for realistic c 260 l.jpg

Intelligence Critical for Realistic C2

  • Intelligence imposes temporal constraints

    • When can a satellite observe?

    • How long to insert surveillance (LRSU)?

    • How long before I must commit to COA?


Intelligence critical for realistic c 261 l.jpg

Intelligence critical for realistic C2

  • Intelligence collection must be focused

    • Commanders must:

      • Prioritize their intelligence needs

      • Understand higher-level intelligence priorities

      • Provide intelligence guidance to subordinates

        e.g. Simulation Information Filtering Tool [Stone et. al]


Brigade planning simplified l.jpg

Brigade Planning (simplified)

  • Attack 2nd echelon tank division (TD)

  • Identify Engagement Area (EA Pad)

    Should canalize OPFOR and restrict movement

  • Identify launch time

    Require 2-hour notice

AA

Lincoln

EA Pad


Brigade pir l.jpg

PL ECHO

Brigade PIR

AA

Lincoln

  • When will TD leave AA Lincoln?

    Verifies enemy intent

  • When will TD reach PL Echo?

    Satisfies the need for 2-hour notice

    Further verifies enemy intent

    Location of PL Echo driven by PIR

2hrs

EA Pad


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PL ECHO

Intelligence Plan

Assembly Area

LRSU Trigger attack: TD 2hrs from EA Pad

SLAR Monitor movement from assembly area

EA Pad


Final brigade plan l.jpg

Final Brigade Plan

Decision

Point

H

H-8

H+3

H-10

H+2

SLAR monitor AA

Insert LRSU

LRSU monitor PL Echo

Deep Attack

Execute Mission

Arrive at EA

Break Contact


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Automating PIR

  • Identify PIR in my own plans

    • Find preconditions, assumptions, and triggering conditions that are dependent on OPFOR behavior

  • Extract PIR from higher echelon orders

    • Specialize as appropriate for my areas of operation

  • Derive tasks for satisfying PIR

    • Sensor placement

  • Ensure consistency of augmented plans


Identifying pir l.jpg

Identifying PIR

  • Examine COA dependencies on OPFOR

    • e.g. Precondition of engaging:

      OPFOR will-be-at EA Pad at time H+2

  • Look for dependencies that:

    • Are not under my direct control

    • Are uncertain

  • Implemented with PIR recognition schema:

    • Abstract rules that scan plans and assert PIR

      • Some domain-independent, some domain-specific


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Interpreting Higher Level Guidance

  • Need to convert into PIR at my echelon

    • e.g. Brigade’s PIR:

      • When will lead regiment reach forward defense

        becomes Battalion PIR

      • When will lead battalion of lead regiment reach fwd def

  • Implemented by specialization rules

    • Encode doctrinal and terrain relationships


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Deriving Sensor Plans

  • Implemented via tactical planning mechanism

    • PIR represented as “knowledge goals”

    • Domain theory augmented with sensing tasks

      • Sensing tasks achieve knowledge goals

      • Tasks encode maneuver / temporal dependencies

    • Planning process fills in details

      • Sensing tasks added to achieve knowledge goals

        • e.g. Observe TD activity near PL_ECHO

      • Other tasks added to satisfy maneuver dependencies

        • e.g. Use UH-60 to insert LRSU near PL_ECHO


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Ensuring Consistency

  • Implemented via tactical planning mechanism

    • If PIR goals cannot be satisfied, COA is invalid

      or

      Use unsatisfied PIR to request external assets

  • Sensing plans constrain timing of events

    • If temporal constraints inconsistent, COA is invalid


Significant results l.jpg

Significant Results


Significant results72 l.jpg

Significant Results

  • Continuous planning paradigm works well for modeling C2 behavior in the joint synthetic battlespaces

    • Dynamic planning, monitoring, and execution

    • Handles situation interrupts in test cases

  • Collaborative planning is made possible by adding a few extensions to a general purpose planner

  • A model of perceptual attention and situation awareness implemented in RWA-Soar pilot

  • Developed a technique for deriving Priority Intelligence Requirements with planner


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Significant Results (2)

  • Publications

    • Continuous Planning and Collaboration for Command and Control in Joint Synthetic Battlespaces, CGF&BR ‘99

    • Deriving Priority Intelligence Requirements for Synthetic Command Entities, CGF&BR ‘99

    • Modeling Perceptual Attention in Virtual Humans, CGF&BR ‘99

    • Perceptual Grouping and Visual Attention in a Multi-agent World, Agents ‘99


Slide74 l.jpg

Scope of Task Coverage

ATKHB Attack Mission

Achieve Tactical Disposition

Reduce Enemy Posture

Achieve Culminating Task

Consolidate

1-4-1305 (Section 6.1.2): Integrate fire support

Attack (METL task)

1-4-1206:

Continuous Tasks

Achieve Readiness

Achieve Physical Posture

1-2-xxxx: Establish satellite comm. (C2)

1-2-xxx0: Establish ground comm (C2)

1-2-7509: Establish voice comm (C2)

11-5-0104: Establish FM radio (C2)

1-4-1001: Perform C2 operations (C2)

1-4-1303: Control tactical operations (C2)

------------------------------------------------------------

1-4-1202: Implement security measures (Int)

1-4-1203: Process intelligence information (Int)

1-4-1311: Liaison operations (Int)

------------------------------------------------------------

1-4-1105: Provide admin services (CSS)

1-2-7708: Provide food support (CSS)

1-2-7710: Operate field mess (CSS)

1-2-7720: Establish med support (CSS)

1-2-7721: Conduct med activities (CSS)

1-4-1102: Perform strength management (CSS)

1-4-1104: Conduct casualty reporting (CSS)

1-4-1308: Direct army airspace C2 (CSS)

1-4-1310: Civil-military operations (CSS)

1-4-1403: Monitor equipment readiness (CSS)

1-4-1406: Provide logistic services (CSS)

1-3:0001: Plan and organize move (Mnv)

1-2-0101: Move to and occupy assembly area (Mnv)

1-4-1306: Establish and maintain tactical command post (C2)

1-2-7726: Conduct FARP operations (CSS)

1-4-1101: Personnel (S1) planning (C2)

1-4-1201: Intelligence (S2) planning (C2)

1-4-1301: Operations (S3) planning (C2)

1-4-1401: Logistics (S4) planning (C2)

1-4-1302: Establish and maintain

tactical operations center (C2)

1-4-1305: Coordinate maneuver with CSS and rear ops (C2)

---------------------------------------------------

1-2-0320: Provide supply support (CSS)

1-2-7723: Perform maintenance (CSS)

1-2-7728: Process ammo and fuel (CSS)

1-4-1103: Replacement operations (CSS)

1-4-1402: Coordinate supply/equip. (CSS)

1-4-1405: Plan and coordinate transport assets (CSS)

Legend

Implemented

Partially implemented

Desire to implement

Less relevant


Expected results l.jpg

Expected Results

  • Detailed evaluation of planner

    • Empirical

    • Analytical

  • Extended model of situation awareness at entity and C2 levels

    • Attention, hierarchical clustering, classification, fusion

  • Extended model of collaboration

  • Abstract technical description of planner

  • Journal articles and conference papers


Measures of success l.jpg

Measures of Success

  • Collective Measure

    • Ability of a group of entities (RWA Battalion) to achieve mission objectives in scenarios containing a wide range of situation interrupts

  • Individual Measures

    • Scalability: size of groups that can act autonomously

    • Flexibility: classes of situation interrupts handled by group behavior

    • Types of multi-agent reasoning integrated into framework

      • i.e., collaborative, adversarial, temporal, ...

    • Breadth and depth of domain knowledge

      • e.g., # of tasks, echelon levels, functional categories (battlefield operating systems)


Evaluation l.jpg

Evaluation

  • Empirical

    • Developed scenario generator, logging function

    • Will collect data from scenarios run in batch mode

    • Encode additional domain knowledge (WARSIM?)

    • Evaluate scalability

  • Analytical

    • Develop abstract description of planner

    • Complexity measures for scalability

    • Analyze properties of collaborative planner -- can it be de-coupled from Soar-CFOR implementation?


Technology transition l.jpg

Technology Transition


Efforts l.jpg

Efforts

  • Formulated concept for C2 in NASM

  • Demo at JPMR in February ‘99

  • Presented 3 papers at CGF&BR, May ‘99

    • Perceptual attention, C2 Modeling, PIR

  • JSIMS/ASTT workshop, May ‘99

    • WARSIM commonality (POC’s: Milks & Karr)

    • ONESAF?


Problem areas l.jpg

Problem Areas


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Focused Efforts Required

  • Not yet addressing role of learning

  • Need good evaluation

    • Scalability, robustness, efficiency, …


Programmatic issues l.jpg

Programmatic Issues


Schedule l.jpg

Schedule

  • Milestone 4: 12/98

    • Design Review 2

      • Approach to learning improved group models

      • Approach to temporal planning


Schedule 2 l.jpg

Schedule (2)

  • Milestone 5: 9/99 (revise to 12/99?)

    • Technology POP Demonstration 3

      • RWA Attack Battalion

      • Demonstrate advanced group understanding

      • Demonstrate more advanced group planning

        • Temporal planning

        • Group understanding: plan recognition

      • Demonstrate advanced group execution

        • Commander utilizes teamwork model (scaled down)

      • Demonstrate group learning

        • Improve group models through experience

    • Deliver software and domain independent descriptions of new capabilities


Demonstration l.jpg

Demonstration


Demonstration scenario l.jpg

Demonstration Scenario

  • Attack Helicopter Battalion (AH-64)

    • Battalion Commander

    • 3 Helicopter Companies

      • Company Commanders

      • Apache Pilots

    • 1 Combat Service Support Commander

  • Deep Attack Mission Scenario

    • Companies move from Assembly Area to Holding Area

    • Situation interrupt: unexpected enemy forces in Holding Area

    • Dynamically re-plan and execute mission


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