Command and Control Modeling for Synthetic Battlespaces: Flexible Group Behavior Randall W. Hill,...

Command and Control Modeling for Synthetic

Battlespaces:Flexible Group Behavior

Randall W. Hill, Jr.Jonathan Gratch

USC Information Sciences InstituteASTT Interim Progress Review

May 24, 1999

Agenda

Synthetic Forces ProblemProgram HypothesesTechnologies and R&DSignificant Results & Expected ResultsTechnology Transition Products & EffortsProblem AreasProgrammatic Issues

Synthetic Forces Problem

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

Develop autonomous command forces Act autonomously for days at a time

Reduce load on human operators

Behave in human-like mannerProduce realistic training environment

Perform C3I functionsReduce the number of human operatorsCreate realistic organizational interactions

Program Hypotheses

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

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

Technologies and R&D

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

Technologies

Situation Awareness Current situation

Need a consolidated pictureRequires situation assessment at multiple echelons

Future situationIntegrate planning with future sensing requirements Formulate Priority Intelligence Requirements (PIR)

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)

BP

FARPCSS

HA

HA

FLOT

SEAD

SLARMLRS

Battalion Deep Attack

….Operations

Order(plan)

C2 Architecture

Battalion Commander

Company ACommander

Company XCommander

Company A

PilotHelicopter

PilotHelicopter

PilotHelicopter

ModSAF

Company X

PilotHelicopter

PilotHelicopter

PilotHelicopter

….

Operations Order(plan)

Operations Order(plan)

Situation Report(understanding)

Situation Report(understanding)

Situation Report(understanding)

PerceptsActions PerceptsActions

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

C2 Entity Architecture

Planner(General Purpose

Reasoner)

Plan Manager Management

Plans

Management Plans

Tactical PlansTactical Plans

ManagementTheory

(domain independent)

ManagementTheory

(domain independent)

Tactical Domain Theory

Tactical Domain Theory

World ModelWorld Model

Situation Assessment

Synthetic Battlespace

Situation Reports, Sensing

Facts, inferencesExpectations

OPORDER Other Communications

Technologies and R&D:Continuous Planning

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

What are Plans?

Hierarchically ordered sequences of tasksPlans 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

Plan Generation Example

Destroyed(Enemy)

Attack(A, Enemy)

Move(A,BP) Engage(A,Enemy)

at(A,BP)at(A,FARP)

at(Enemy,EA)

at(A,BP) Destroyed(Enemy)

Destroyed(Enemy)

at(A,FARP)

at(Enemy,EA)

World Model

. . .

init

Company A plan

Company B plan CSSplan

Move Move Move

Move Move Move Move

Engage EngageReturn ReturnMove

OPFOR Plan

Move Move

Move

Battalion Tactical Plans

CoDeep Attack

CoDeep Attack

FARPOperations

Situation Interrupts Happen!

destroyed(Enemy)

Attack(A, Enemy)

Move(A,BP) Engage(A,Enemy)

at(A,BP)at(A,FARP) at(A,BP) destroyed(Enemy)

destroyed(Enemy)

at(A,FARP)

at(Enemy,EA)

Current World

active(A)

Star

t of

OP

ADA

Attack

active(A)active(A)

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

Technologies and R&D:Collaborative Planning

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

Move(A,BP) Engage(A,Y)

Dead(Y)

Move(CSS,HQ)

at(CSS,HQ)at(CSS,FAA)

at(gas,FAA) at(gas,HQ)

at(A,BP)at(A,FAA) at(A,BP)

at(gas,FAA)

Op e

rati

on B

egin

s

Combat Service Support Plan

Attack Helicopter Company Plan

resupplied(HQ)

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-servingAdversarial

Try to introduce conflict in other agent’s plan

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

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

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

Must model how stances influence planning How do we alter COA generation

C2 Entity Architecture

Planner(General Purpose

Reasoner)

Plan Manager Management

Plans

Management Plans

Tactical PlansTactical Plans

ManagementTheory

(domain independent)

ManagementTheory

(domain independent)

Tactical Domain Theory

Tactical Domain Theory

World ModelWorld Model

Situation Assessment

Synthetic Battlespace

Situation Reports, Sensing

Facts, inferencesExpectations

OPORDER Other Communications

When to Use a Stance

Model the collaborative planning process Includes management tasks that modulate the

generation of tactical plansTasks refer to specific tactical plansSpecify preconditions on changing stance

Includes knowledge of one’s organizational role

Planner constructs management plans Use same mechanisms as tactical planning

Management Plan Example Explicitly model the Military Decision Making

Process

COADevelopment

Authoritative towards subordinatesDeferential towards superiorsAdversarial towards OPFOR

COAAnalysis

Authoritative towards OPFORAdversarial towards self (war gaming)

Tasks Stances

Implementing Stances

Implemented as search control on planner Plan manager

Takes executing management tasksGenerates 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

Move(A,BP)

Move(CSS,HQ)

at(CSS,HQ)at(CSS,FAA)

at(gas,FAA) at(gas,HQ)

at(A,BP)at(A,FAA)

at(gas,FAA)

Init

ial S

tate

PlannerRetract

Retract

Deferential towards

Combat Service Support Plan

Make CSS Planner defer to Company A’s Plan

Manager

C2 Entity Architecture

Planner(General Purpose

Reasoner)

Plan Manager Management

Plans

Management Plans

Tactical PlansTactical Plans

ManagementTheory

(domain independent)

ManagementTheory

(domain independent)

Tactical Domain Theory

Tactical Domain Theory

World ModelWorld Model

Situation Assessment

Synthetic Battlespace

Situation Reports, Sensing

Facts, inferencesExpectations

OPORDER Other Communications

Technologies and R&D:Situation Awareness

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

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

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

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

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)

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

Perceptual Grouping

PreattentiveGestalt grouping

Involuntary Proximity-based Other features

DynamicVoluntary grouping

K

K

K

Group Features

Quantity and compositionActivity

Moving Shooting

Location Center-of-mass Bounding-box

Geometric relationships wrt pilot Slant-range, azimuth, etc.

High Resolution

Entity Features

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

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)

Sea

LandOverwatchPosition

OverwatchPosition Transport Carrier

Escort Carrier

Rendezvous Point

Escort task• Orient on group

• Voluntary grouping

Goal-driven Attention

Low Resolution High Resolution

Stimulus-driven Attention

Situation Awareness at Higher Echelons

Command Entity

Command Entity

Command Entity

Situation Reports Situation Reports

Situation Reports

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

Bottom-up and top-down approachBottom-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

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

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

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 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 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 C2

Intelligence collection must be focused Commanders must:

Prioritize their intelligence needsUnderstand higher-level intelligence prioritiesProvide intelligence guidance to subordinates

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

Brigade Planning (simplified)

Identify Engagement Area (EA Pad)Should canalize OPFOR and restrict movement

Identify launch time Require 2-hour notice EA Pad

AALincoln

Attack 2nd echelon tank division (TD)

PL ECHO

Brigade PIR

When will TD leave AA Lincoln?Verifies enemy intent

When will TD reach PL Echo? Satisfies the need for 2-hour noticeFurther verifies enemy intentLocation of PL Echo driven by PIR

EA Pad

AALincoln

2hrs

EA Pad

PL ECHO

Intelligence Plan

SLAR Monitor movement from assembly area

LRSU Trigger attack: TD 2hrs from EA Pad

Assembly Area

Final Brigade Plan

Execute Mission

Arrive at EA

Break Contact

DecisionPoint

H H+2 H+3H-8H-10

Insert LRSU LRSU monitor PL Echo

Deep Attack

SLAR monitor AA

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

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

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 PIRWhen will lead battalion of lead regiment reach fwd

def

Implemented by specialization rules Encode doctrinal and terrain relationships

Deriving Sensor Plans

Implemented via tactical planning mechanism PIR represented as “knowledge goals” Domain theory augmented with sensing tasks

Sensing tasks achieve knowledge goalsTasks encode maneuver / temporal dependencies

Planning process fills in detailsSensing tasks added to achieve knowledge goals

• e.g. Observe TD activity near PL_ECHOOther tasks added to satisfy maneuver dependencies

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

Ensuring Consistency

Implemented via tactical planning mechanism

If PIR goals cannot be satisfied, COA is invalidor

Use unsatisfied PIR to request external assets

Sensing plans constrain timing of events If temporal constraints inconsistent, COA is invalid

Significant Results

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

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

Scope of Task Coverage

ATKHB Attack MissionAchieve Tactical

Disposition

Reduce Enemy Posture

Achieve Culminating

Task

Consolidate

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)

Achieve Readiness

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)

Achieve Physical Posture

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

Attack (METL task) 1-4-1206:

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)

Continuous Tasks

Legend

Implemented

Partially implemented

Desire to implement

Less relevant

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

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

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

Efforts

Formulated concept for C2 in NASMDemo at JPMR in February ‘99Presented 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

Focused Efforts Required

Not yet addressing role of learningNeed good evaluation

Scalability, robustness, efficiency, …

Programmatic Issues

Schedule

Milestone 4: 12/98 Design Review 2

Approach to learning improved group modelsApproach to temporal planning

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

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