The Loaded Loop:A Complex Adaptive Systems (CAS) Model

of Command and Control (C2) Processesin Combat

  

by Paul J. Hiniker, Ph.D.

C4I Modeling, Simulation & AssessmentDefense 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? (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

Predictions Lens

Descriptions Lens

Schema

Prescriptions Lens

Ground Truth

COP Schema Description

Perception

Command Center Schema and Congruity of Situation Assessment

Cognitive Domain

InformationalDomain

PhysicalDomain

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

Combat Decision LoopXf = Df

Blue Quality Decision Loop Speed

1.0

(Utiles/minute)

Red LossesTotal Losses

(%)

C2 Decision-Making and the OODA Loop:

Quality Decision Loop Speed (Df) on Battlefield Exchange Ratio (Xf)

Df

Xf

Df = 100(C x R)/(tC+ tR+ tA+ tB) -- (2) Quality Decision Loop Equation

R = Reliability of COA Forecast , tR from Wargame Simulation Schema Prescription

C = Situation Awareness, tC from COP Schema Description

tB = Time to FeedbacktA = Action Time

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

Decision Information Superiority

DISf = Cf – Ce (3.2)

Congruity of Red View

1.0

Congruity of Blue View

Cf

DISf

(%)

Ce(%)

Corollaries• Requires active sensors and communications for this critical information•Suggests a focused strategy for Info Ops

Narrower Decision Information Superiority

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)

Df = log Pfor 0 P

Pace of Battle (P)

(Workload)

Quality Decision Loop Speed (Df)

Impact of Pace of Battle (P) on Quality Decision Loop Speed (Df)

(Performance)

(Yerkes-Dodson Law)

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.

The Looming C2 Cliff

Quality Decision Loop Speed (Df) and Pace of Battle (P) on Battlefield Exchange Ration (Xf)

Df

Xf

log P

D1

D2 D3NS

NP

NS

NP

NS

NP

Effective Quality Decision Loop Speed (Ds) for Nested Command Centers Sharing COP Schema

Ds = ( d (Ns Np ) ) (6.0) Nested Command Centers Equation

NS = Shared AwarenessNP = Shared Plans

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

Results from Three Military Exercises with Shared “COP” Schema, 1997-1998

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.