Data Mining Combat Simulations: Data Mining Combat Simulations: an - PowerPoint PPT Presentation

Data Mining Combat Simulations: Data Mining Combat Simulations: an Emerging Opportunity an Emerging Opportunity Barry A. Bodt babodt@arl.army.mil (410) 278-6659 Computational and Information Sciences Directorate Army Research Laboratory (ARL) The U.S. Army’s Corporate Laboratory

Motivation Motivation Motivation • Simulation and statistical analysis are underutilized in helping the commander’s staff to analyze courses of action. • Battle results are infinite in scope, yet the outcome of any one battle is defined by a unique set of battlefield interactions. • Key is to recognizing those interactions through development of more informative performance measures unique to the scenario at hand.

Approach Approach Approach Use statistical methods Use statistical methods and combat models to and combat models to create a methodology create a methodology that identifies non- - that identifies non traditional metrics for traditional metrics for plan evaluation. plan evaluation.

Background Background Background Military Decision Making Process Military Decision Making Process Military Decision Making Process • Focus on Focus on wargame wargame • • Disciplined rules • Disciplined rules • Synchronization matrix Synchronization matrix • COA COA

Joint Tactical Operation Center, Qatar Joint Tactical Operation Center, Qatar Joint Tactical Operation Center, Qatar

Network Centric Warfare Network Centric Warfare Network Centric Warfare Communicate… Communicate… Smart Logistics Smart Logistics On- -board Diagnostics board Diagnostics On Soldier Health Soldier Health Sensor information Sensor information … …

Information Requirements in NCW Information Requirements in NCW Information Requirements in NCW The key to any analysis is the set of measures used to The key to any analysis is the set of measures used to represent the performance and effectiveness of the represent the performance and effectiveness of the alternatives being considered. We are relatively good at alternatives being considered. We are relatively good at measuring the performance of sensors and actors, but measuring the performance of sensors and actors, but less adept at measuring command and control. less adept at measuring command and control. Command and control, to be fully understood, cannot Command and control, to be fully understood, cannot be analyzed in isolation, but only in the context of the be analyzed in isolation, but only in the context of the entire chain of events that close the sensor- entire chain of events that close the sensor -to to- -actor actor loop. To make this even more challenging, we cannot loop. To make this even more challenging, we cannot isolate on one target, or even a set of targets but need isolate on one target, or even a set of targets but need to consider the entire target set. Furthermore, network to consider the entire target set. Furthermore, network centric warfare is not limited to attrition warfare … It is centric warfare is not limited to attrition warfare … It is not sufficient to know how many targets are killed, but not sufficient to know how many targets are killed, but exactly which ones and when… exactly which ones and when… Ref: Network Centric Warfare, 2002 Ref: Network Centric Warfare, 2002

Simulation Data Simulation Data Simulation Data • Scenario development • OneSAF lay down of forces • OneSAF modified output • Data supporting modeling

Scenario Scenario Scenario BMP-2 BMP-2 BMP-2 T-72M T-80 Town T-72M T-72M T-72M T-80 T-72M T-80 T-80 Company Objective

OneSAF Screen Dump OneSAF Screen Dump OneSAF Screen Dump

Automated Data Collection Automated Data Collection Automated Data Collection • OneSAF Modifications OBJECT_ID: 100A31 X = 24396.82 Y = 25828.75 Z = 755.72 Vehicle Authorized Undamaged Catastrophic Firepower Mobility Damage Damage Damage M2 1 0 1 0 0 Equip/Supplies: Current Lvl Resupply Lvl Avg Per Veh 25mm HE (M792) 625.00 625.00 625.00 25mm APFSDS-T (M919) 325.00 325.00 325.00 TOW (TOW) 0.00 5.00 0.00 7.62mm MG (M240) 2340.00 2340.00 2340.00 Fuel (Fuel) (gallons) 171.00 174.00 171.00

OneSAF Modification Modification OneSAF OneSAF Modification Killer/Victim Scoreboard Killer/Victim Scoreboard Killer/Victim Scoreboard • Firer and Target Identity and Location • Firer and Target Identity and Location • Type of Ammo Type of Ammo Time Stamp 1010070890 • Vehicle ID 1076 • Range • Range Firer ID 1087 • Outcome Outcome • Projectile 1143670848 Firer Position: X = 220217.00 Y = 146765.00 Z = 12.37 Target Position: X = 222454.38 Y = 149117.80 Z = 9.99 Vehicle 1076: Hit with 1 "munition_USSR_Spandrel" (0x442b0840) Comp DFDAM_EXPOSURE_HULL, angle 19.53 deg Disp 0.889701 ft Kill Thermometer is: Pk:1.00, Pmf:1.00, Pf:0.90, Pm:0.80 Pn:0.80 RANGE 3246.773576 r = 0.990835 kill_type = MF 1076 100A41 vehicle_US_M1 1087 100A23 vehicle_USSR_BMP2

Data Supporting Classification Models Data Supporting Classification Models Data Supporting Classification Models Response – – mission mission Response • 228 OneSAF runs accomplished (success) accomplished (success) • 3 situational snapshots per if an undamaged platoon if an undamaged platoon run occupies objective at occupies objective at – 10% blue ammo expended battle end (MA) battle end (MA) – 25% blue ammo expended – 40% blue ammo expended - other responses include other responses include - • 429 data points per run (143 MBT and “Eric” strength MBT and “Eric” strength per stopping time) and forces on objective and forces on objective – Number of K, M/F, F, and M kills – Ammunition levels – Number of hits delivered Data Matrix Data Matrix – Range of hits – Number of side hits delivered 228 x 434 228 x 434 – Distance to objective – Number of Blue on objective

Model Performance Model Performance Model Performance Slice 1 ~ 2000m Slice 1 ~ 2000m Slice 2 ~ 4000m Slice 2 ~ 4000m Or ~ 5 ½ minutes Or ~ 5 ½ minutes Correctly Classified Correctly Classified Or ~ 10 minutes Or ~ 10 minutes Correctly Classified Correctly Classified Loss: 71% Loss: 71% Slice 3 ~ 5800m Slice 3 ~ 5800m Loss: 82% Loss: 82% Pred 0 1 Win: 68% Win: 68% Pred Or ~ 20 minutes Obs 0 1 Or ~ 20 minutes Win: 77% Win: 77% Correctly Classified Correctly Classified Overall: 70% Obs Overall: 70% Overall: 80% Overall: 80% 85 34 0 Loss: 88% Loss: 88% 98 21 0 Pred 0 1 Win: 82% Win: 82% 35 74 1 Obs 25 84 1 Overall: 85% Overall: 85% 105 14 0 20 89 1 Company Objective Company Objective Company Objective

Method Comparison Method Comparison Method Comparison Percent Correct Classification Percent Correct Classification by Stopping Time and Method by Stopping Time and Method Stopping Discriminant CART Logistic Time (min) Analysis Regression 5 ½ 70% 70% 69% 10 80% 75% 74% 20 85% 82% 85%

Advantages Advantages Advantages – Support prediction for COA performance evaluation – Provide models identifying key battle parameters for a given engagement, influencing both COA development and commander’s critical information requirements – Input to CCIRs – Input to contingency plans – Input to tolerances for synchronization

Implementation Models Implementation Models Implementation Models Reach back Reach back Advantages Advantages computational power (ARL 9 th th ) -computational power (ARL 9 ) - -more complex analyses more complex analyses - Distributed Distributed Disadvantages Disadvantages -latency - latency Advantages Advantages -can’t smell gunpowder can’t smell gunpowder - -cheaper boxes (250 cheaper boxes (250 OneSAF OneSAF - boxes used at Ft. Leavenworth) boxes used at Ft. Leavenworth) -closer to action - closer to action Disadvantages Disadvantages -depth of a field analysis depth of a field analysis - -automation required automation required -

Why Aren’t We Already Doing This? Why Aren’t We Already Doing This? Why Aren’t We Already Doing This? A few reasons … A few reasons … • Computer simulation focus has been mainly strategic or oriented toward acquisition. Tactical application has been limited. • Simulations did not have high enough fidelity for tactical application. • Simulations were unstable. • Computing resources were inadequate. • Necessary communication of inputs had not been imagined. • Simulation creators do not always talk to statisticians.

Improvements Here and On the Way Improvements Here and On the Way Improvements Here and On the Way • Stability • Power Point force laydown of forces • MS Word OPORD • Terrain, weather wizzards • Composable simulations • After Action Report data • Man-in-loop allowed • Sensor advances • Communication advances • Computation speed and cost