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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 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 • Significant Results & Expected Results • Technology Transition Products & Efforts • Problem Areas • Programmatic Issues
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 manner • Produce realistic training environment • Perform C3I functions • Reduce the number of human operators • Create realistic organizational interactions
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 • 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 picture • Requires situation assessment at multiple echelons • Future situation • Integrate 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)
Battalion Deep Attack MLRS SLAR SEAD HA BP HA CSS FLOT FARP
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
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 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
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 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
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)
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
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 • 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
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) 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
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
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 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 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 • 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 • 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 • 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 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 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
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!
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)
K K K Perceptual Grouping • Preattentive • Gestalt grouping • Involuntary • Proximity-based • Other features • Dynamic • Voluntary grouping
Group Features • Quantity and composition • Activity • Moving • Shooting • Location • Center-of-mass • Bounding-box • Geometric relationships wrt pilot • Slant-range, azimuth, etc.
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 • 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)