1. A Complex Adaptive Systems (CAS) Model
The Loaded Loop:
A Complex Adaptive Systems (CAS) Model
of Command and Control (C2) Processes
in Combat
by Paul J. Hiniker, Ph.D.
C4I Modeling, Simulation & Assessment
Defense Information Systems Agency
Arlington, VA 22203
Presented at the RAND
Modeling of C2 Decision Processes Workshop
July 31, 2001, McLean, VA

2. Problem: What are the causal effects of C4ISR on combat outcomes
Problem: What are the causal effects of C4ISR on combat outcomes? (PBD 070C)
Focus: C2 decision-making
Aim: JWARS Simulation

3. Impact of C4ISR on Combat Outcome: Overview
A Complex Adaptive System/Lanchester Model (Dr. Hiniker)
7/31/01

4. Approach: Command Center as Complex Adaptive System (CAS) with Schema
Act
Predictions Lens
Descriptions Lens
Schema
Prescriptions Lens
Monitor

5. Command Center Schema and Congruity of Situation Assessment
Cognitive Domain
Perception
Informational
Domain
COP Schema Description
Physical
Domain
Ground Truth

6. Weaponry and Lanchester Force Equations
In combat modeling, C2 factors, such as use of shared COP schema, are viewed as multipliers of the force coefficients, Cf and Ce, in Lanchester equations:
dF/dt = -CeE and
(1) Lanchester Force Equations
dE/dt = -CfF, where
F = friendly (Blue) force size and Cf = friendly kills/sec/unit.
E = enemy (Red) force size and Ce = enemy kills/sec/unit

7. C2 Decision-Making and the OODA Loop:
Quality Decision Loop Speed (Df) on Battlefield Exchange Ratio (Xf) Xf
1.0
Red Losses
Total Losses
(%)
Combat Decision Loop
Xf =  Df
C = Situation Awareness, tC from COP Schema Description
Blue Quality Decision Loop Speed Df
R = Reliability of COA Forecast , tR from Wargame Simulation Schema Prescription
(Utiles/minute)
tA = Action Time
tB = Time to Feedback
Df = 100(C x R)/(tC+ tR+ tA+ tB) (2) Quality Decision Loop Equation

8. C2 Combat Decision Superiority Derivation from Lanchester Equations DSf = (Cf x Rf) tDe / (Ce x Re) tDf where tD = t C + t R + tA + tB
Narrower Decision Information Superiority Cf
1.0
Decision Information Superiority
DISf = Cf – Ce (3.2)
DISf
Congruity of Blue View
(%)
Corollaries
Requires active sensors and communications for this critical information
Suggests a focused strategy for Info Ops
Congruity of Red View Ce
(%)

9. Results from Three Controlled Experiments with Shared COP Prototypes, 1990-1991
Scenario: Air/Sea battle set in Persian Gulf using RESA Wargame Simulator
Exp Treatment: All parties share big and little pictures fed by national and organic sensors.
Control Treatment: Big picture from national sensors at CJTF. Little pictures from organic sensors at ship captains.
Constant weaponry with experimentals and controls.
1990 COP Prototype
·      improved situation assessment accuracy (Cf from commander’s sketch)
·      improved shared awareness (Ns from opinion reports)
·      improved synchronization of action (TA, +10% speed)
1991 COP Prototypes
·      improved battlefield exchange ratio (Xf, +25%)
 While controlling for weaponry, use of shared COP schema causes improved combat effectiveness (cf. IS Value Chain)

10. Impact of Pace of Battle (P) on Quality Decision Loop Speed (Df)
Df = log P
for 0  P  
Quality Decision Loop Speed (Df)
(Performance) 
Pace of Battle (P)
(Yerkes-Dodson Law)
(Workload)

11. Results from Controlled Experiment on Bounded Rationality with Variable Threats, 1987
Scenario: Identification of first arriving air threat from several on tactical air defense display.
Exp Treatment: 4 simultaneous threats at 12 different arrival speeds.
Control Treatment: 7 simultaneous threats at 12 different arrival speeds.
·      Finding: For both threat conditions, subjects performance followed Yerkes-Dodson growth curve which peaked at T* = 2.2 seconds/threat
 Human decision-making performance is limited by number and speed of decision elements.

12. Xf Df  log P The Looming C2 Cliff
Quality Decision Loop Speed (Df) and Pace of Battle (P) on Battlefield Exchange Ration (Xf) Df Xf 
log P

13. Effective Quality Decision Loop Speed (Ds) for Nested Command Centers Sharing COP Schema
Act
Monitor D1
NS = Shared Awareness
NP = Shared Plans NS NS NP NP D2 D3 NS NP
Ds =  ( d (Ns Np ) ) (6.0) Nested Command Centers Equation

14. Results from Three Military Exercises with Shared “COP” Schema, 1997-1998
Scenario
Exp Treatment
Comparison Group
Findings
1997 Air Force Exercise
JTIDS Equipped Aircraft
No JTIDS on Aircraft
250% improvement in kill ratios for 12,000 sorties
1998 Navy Fleet Battle Experiment
Shared COP between Army Helicopters, Air Force AC 130s, and Navy Units
No Shared COP
Improved combat power and faster mission accomplishment, TA improved 50%.
1998 Army Task Force XXI Exercise
Shared tactical Internet
No tactical Internet
Improved combat power and 10 fold increase in lethality
 Even with similar weaponry, sharing a more complete picture of the battlespace is positively correlated with improved combat effectiveness

15. Needed Results from Controlled Experiment with Shared Planning
* Controlled experimentation affords the only method for unequivocal testing of causal hypotheses
Scenario: Air/Sea battle set in Persian Gulf with CJTF on carrier and two ship captains.
Exp Treatment: CJTF and both ship captains comprise a CAS sharing COP schema fed by organic sensors and overhead surveillance and reconnaissance and with shared CAP white board for collaborative planning.
Control Treatment: Big picture from national sensors at CJTF. Little picture from organic sensors at ship captains. Phone communications.
Constant weaponry with experimentals and controls.
Expected Results: Higher Df and higher Xf in experimental condition; much higher Df and Xf with self organization upon withdrawing CJTF from operation.