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

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

Impact of C4ISR on Combat Outcome: Overview A Complex Adaptive System/Lanchester Model (Dr. Hiniker) hinikerp@ncr.disa.military, 7/31/01

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

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

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

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

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 (%)

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)

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)

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.

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

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

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

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.