Title: Models, Gaming, and Simulation Session 6
1Models, Gaming, and Simulation - Session 6
- Aggregated Attrition Models -
- Non-Lanchester Approaches
2Topics
- Force Ratio models of attrition
- Firepower Scores / WEI/WUVs
- Correlation of Forces
- Potential-Antipotential Method
- Hierarchical Attrition Algorithms
- Next Session Review
3Force Ratio Attrition Models
- CONCEPT
- Summarize effectiveness in combat with a single
scalar measure of combat power for each unit. - When combat occurs, use the ratio of attacker's
to defender's measures to determine the outcome - Measures can be very subjective, or based on
summary characteristics of unit equipment, or
based on a weighted combination of weapon
firepower, mobility, vulnerability, etc.
4Force Ratio Approach - Firepower Scores
- CONCEPT Assign a firepower score to each weapon
system and sum these scores for each weapon
system on hand in a unit - DEFINITIONS
- n number of distinct types of weapon systems in
a unit - Xi number of systems of type i (i1,2,...,n) in
a unit - Si firepower score for each weapon of type i
-
5Force Ratio Approach - Limitations of Firepower
Scores
- Weapon system interactions ("synergisms") are not
represented - FPI is additive across weapon types (e.g.,
FPI100 derived from 15 tanks, 30 infantry
fighting vehicles and 6 mortars equals FPI100
derived from 30 tanks). - FPI is linear in the number of weapons - cannot
directly represent - Minimum unit size required for effectiveness.
- Diminishing returns with large numbers of
systems. - Weapon system types become submerged in the FPI
formula - Illogical battles can occur (e.g., Arty Bn FPI80
defeats Tank Co FPI30). - Validity is suspect because
- Specification of firepower scores is arbitrary
- Force-Ratio predictive power is not validated by
empirical historical research. - Then why are we learning about Firepower Scores?
- Because they match the rule-of-thumb approach
often used by military planners. - Because you need to know enough about them to
note when they are misused.
6Force Ratio Approach - Determining Firepower
Scores
- Alternate Approaches
- Use historical data about combat performance
(1950s analysis) - Use technical measures of weapon firepower
(ATLAS) - Use situationally-dependent technical firepower
measures - Use weighted combinations of firepower, mobility,
vulnerability, reliability, etc., where weights
were assigned by "Delphi" analysis (consensus of
"experts"). This approach uses the term WEI/WUV
(pronounced "wee-wuv") - WEI Weapon Effectiveness Index
- Weapon scores are given without regard to
opposing target types - WUV Weighted Unit Value
- Units are given a base value by summing the WEIs
of all their weapons - Unit values are weighted by subjective ratings
(e.g., for training, morale, C2 systems) - Simple, but very subjective
- Use a measure of what the weapon can kill
(potential/antipotential method)
7Force Ratio Approaches - Correlation of Forces
- Used primarily in planning, not in combat models
- Used in Soviet-style operations planning to
allocate forces to a subordinate for a combat
mission. - Similar approach used in U.S. operations planning
to estimate whether various parts of a plan are
feasible. - Could be used in a model where attrition is not
the focus.
8Force Ratio Attrition Models - U.S. Army
Capability Analysis
- A base type unit is selected and given the combat
value 1.0 - Units are assigned subjective values based on
their perceived strength compared with base unit
type, considering - Primary type of equipment in unit (e.g., M1A1
versus M1 versus M60A3), - Percent strength authorized, and
- Modifications subjectively based on intel
estimate and current status of own unit. - Ratio of friendly to enemy estimated combat power
is used to infer the capabilities of the friendly
force. - Example U.S. Division planning for an operation
against a threat division using Soviet-style
equipment and organization.
9Force Ratio Attrition Models - U.S. Army
Capability Analysis Example
- U.S. Comparison Values (with respect to a BTR
Battalion) - Maneuver
- M113 Bn 1.5
- M2 Bn 2.0
- M1A1 Bn 3.15
- M1 Bn 3.0
- M60A3 Bn 2.25
- ACR Sqdn 2.75
- Div Cav Sqdn 1.5
- Div Cav Sqdn(h) 2.0
- Atk Hel Bn (AH64) 4.0
- Atk Hel Bn (AH1) 3.0
- Artillery
- MLRS Battery 2.0
- 155mm SP Bn 2.0
NOTE 1 All units are given an estimated value
with respect to a BTR Battalion NOTE 2 The unit
commander and operations officer are advised to
develop their own table to allow them to take
into consideration local knowledge about the
situation. This table does not contain real
planning data, but only notional data. (Example
taken from US Army CGSC ST 100-9)
10Force Ratio Attrition Models - U.S. Army
Capability Analysis Example
- Planning Rules of Thumb for Force Capabilities
11Force Ratio Attrition Models - U.S. Army
Capability Analysis Example
- Threat Comparison Values
- Maneuver
- BTR Bn 1.0 (Baseline unit)
- BMP Bn 1.5
- Tk Bn ITR TR ITB MRR
- T-80 2.42 1.56 2.0 2.0
- T-64 2.23 1.44 1.86 .86
- T-72 1.86 1.20 1.55 1.55
- T-62 1.24 .80 1.0 1.0
- T-55 1.0 .64 .83 .83
- AT Bn 1.0
- Atk Hel Sqdn 2.0
- Artillery
- 122mm or 152mm Bn 2.0
- MRL Battery 1.0
ITR Independent Tank Regiment TR Tank
Regiment ITB Independant Tank Battalion MRR
Motorized Rifle Regiment
12Force Ratio Attrition Models - U.S. Army
Capability Analysis Example
- 53 Mech Division
- Maneuver
- TYPE BN VALUE TOTAL
- M113 4 1.5 6.0
- M2 1 2.0 2.0
- M1 2 3.0 6.0
- M60 3 2.25 6.8
- Cav 1 1.5 1 .5
- Atk Hel 1 3.0 3.0
- TOTAL 25.3
- X Strength X .9
- Relative Cbt Power 22.8
-
- Ratio for Maneuver 22.8 22.2 11
- Artillery
- TYPE BN VALUE TOTAL
- 155(SP) 3 2.0 6.0
- MLRS 1 2.0 2.0
- TOTAL 8.0
27 Gds Motorized Rifle Division
Maneuver TYPE BN VALUE TOTAL BTR
6 x 1.0 6.0 BMP 3
x 1.5 4.5 T64(MRR) 3 x 1.8
5.4 T64 (TR) 3 x 1.4 4.2 T64
(ITB) 1 x 2.0 2.0 Div Recon
1 x 1.6 1.6 AT Bn 1 x 1.0
1.0 Atk Hel 1 x 3.0
3.0 TOTAL 27.7 X Strength
X .8 Relative Cbt Power
22.2 Artillery TYPE BN VALUE
TOTAL 122(SP) 2 x 2.0
4.0 122(T) 4 x 2.0
8.0 152(SP) 1 x 2.0
2.0 MRL Btry 3 x 1.0
3.0 TOTAL 17.0 X Strength
X .8 Relative Cbt Power
13.6
13Attrition Coefficient Calculation - Potential /
Anti-potential ("Eigenvalue") Method
- A way to assign firepower scores.
- Avoids the problem of assigning scores based only
on weapon's own characteristics, not on opposing
targets' characteristics. - Avoids some problems of subjectivity.
- CONCEPT Let the value of a weapon system be
directly proportional to the rate at which it
destroys the value of enemy weapon systems. - NOTE Problem reduces to system of simultaneous
linear eqns.
14Attrition Coefficient Calculation - Potential /
Anti-potential Method
- DEFINITIONS
- Force X fights Force Y
- Xi weapons of type i in X force, i 1,2,...,m
- Yj weapons of type j in Y force, j 1,2,...,n
- SXi value of one type i weapon in X force
- SYj value of one type j weapon in Y force
- Kij rate at which one Xi system kills Yj
systems - i1,2,...,m j1,2,...,n
- Lji rate at which one Yj system kills Xi
systems - i1,2,...,m j1,2,...,n
- NOTE Kij and Lji are determined from
killer-victim scoreboards from a high-resolution
model. This implies great dependency on the
high-res scenario, e.g., force structures,
missions, terrain, etc. - So FPIX ?i SXi Xi and FPIY ?j SYj Yj
15Attrition Coefficient Calculation - Potential /
Anti-potential Method
- The above concept and definitions lead to a
system of simultaneous equations - for all j, cY ??SYj ?iLji SXi
- for all i, cX ??SXi ?jKij SYj
- This is a system of mn equations in mn2
unknowns, since the two proportionality constants
cX and cY are not specified. - In matrix notation
- (1) cY ?SY L SX
- (2) cX ?SX K SY
16Attrition Coefficient Calculation - Potential /
Anti-potential Method
- Solving for SY in eqn (1) and substituting in eqn
(2) - cY cX?SX K L SX
- Similarly for SX
- cX cY?SY L K SY
- Let cX cY? ?, then
- ? SX K L SX (eqn 3)
- ? SY L K SY (eqn 4)
- This is a pair of eigenvalue problems for K L
(mxm) and L K (nxn) where the eigenvalue is ? and
eigenvectors are SX and SY .
17Attrition Coefficient Calculation - Potential /
Anti-potential Method
- Problem Solutions are not unique (mn2
unknowns, with mn equations). In fact, they are
only unique to a scaling factors MX for X and MY
for Y. - A Solution Let and set SXi 1.0 for some
weapon Xi which is a major contributor to killing
many Yj systems. This can be shown not to change
the overall Force Ratio as Mx and MY vary, so
the solution is appealing.
18Matrix Algebra Review Eigenvalues and
Eigenvectors
- GIVEN a set of linear equations in unknown
variables xij such that ? I X A X
for some constant ? - DEFINE ? as an eigenvalue and X as an
eigenvector. - THEOREM due to Frobenius guarantees that
- 1. There exists a real, non-negative, largest
eigenvalue ?, and - 2. There exist non-negative eigenvectors (SX and
SY in our formulation) which are unique up to a
scale factor.
19Matrix Algebra Review Eigenvalues and
Eigenvectors
- SOLUTION PROCESS for 2x2 matrix
- 1. Solve for ?
- Characteristic polynomial is
- Let d1 c11c22 and d0 c11c22 - c12c21, then
- 2. Substitute for ? in equations (3) and (4) and
solve for Xij.
20Attrition Coefficient Calculation - Potential /
Anti-potential Example
- GIVEN
- X force of 2 systems, strengths X1 200, X2
150 - Y force of 2 systems, strengths Y1 75, Y2 100
- X1 kills Y1 at rate .03, Y1 kills X1 at rate .04
- X1 kills Y2 at rate .05, Y1 kills X2 at rate .02
- X2 kills Y1 at rate .03, Y2 kills X1 at rate .04
- X2 kills Y2 at rate .02, Y2 kills X2 at rate .01
- So
-
- for ?? cX cY , solve for ? in ?SX K L SX
-
21Attrition Coefficient Calculation - Potential /
Anti-potential Example
- d1 .0032 .0008 .004, and
- d0 (.0032 .0008) - (.0011 .0020)
.00000036 - ? .5(.004 sqrt(.0042 - 4 .00000036) )
- ? max(?1, ?2) .003907878
- Let SX1 1.0
- Let
- Since ? SX K L SX, then
- ( K L - ??I ) SX 0
- Since SX1 1.0, we can solve for SX2 in two
ways - -.000707878SX1 .0011SX2 0
- or .002SX1 - .003107878SX2 0
- Either way gives SX2 .64353
22Attrition Coefficient Calculation - Potential /
Anti-potential Example
- Now solve for SY1 and SY2 using eqn (1) cY SY
L SX -
- so,
- Now compute FPIX and FPIY, and then FR
- Now to assess actual casualties lost by the X and
Y forces, enter a table indexed by FR (and
perhaps other factors) to find a percent of force
lost. Apply this percentage to each weapon type.
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24Attrition Coefficient Calculation - Potential /
Anti-potential Comments
- Solutions are scenario-dependent
- Kill rates must be generated with respect to X
and Y posture and actions (e.g., X attacking Y in
a prepared defensive position, versus X delaying
against Y's attack) - Changes in kill rates are hard to understand.
- In fact, scores sometimes vary greatly with small
changes to a few inputs, and occasionally the
score of a major weapon system will be zero. - This method has the advantage of automatic
adjustment of weapon scores, preventing poor
judgement from influencing the outcome, but the
related disadvantage is that its computations are
obscured by the eigenvalue method. But also,
remember that historical analysis shows little or
no relation of force ratios to battle outcome.
25Hierarchical Attrition Algorithms
- Most combat models have the characteristic that
higher-resolution models feed them with data. - High-resolution models need PH's and PKHs which
are usually supplied by AMSAA and ARL engineering
models. - Medium and low-resolution models usually depend
on kill rates from high-resolution models or
occasionally on engineering models. - Some low-resolution models depend on kill rates
generated by medium-resolution models, e.g.,
ATCAL (Attrition Calibration) links the
medium-resolution COSAGE with the low-resolution
CEM.
26Hierarchical Attrition Algorithms
- A hierarchy of ground combat models was proposed
and partially built by the Army in the 1970s and
1980s, but never reached completion because of
enormous technical difficulties - The vision was a semi-automated way of getting
input data for low-res models from high-res
models, so low-res modelers would not have to
request special runs from high-res modelers
(usually in different organizations). - Too much variation in scenarios, force
structures, weapons, and postures meant that
libraries of high-res results were too hard to
build. - Additionally, organizations resisted getting
"answers" from "black-box" models they could not
influence. - ATCAL is one of the few examples of an existing
formal link between models of differing
resolution for the purpose of generating input
data from the high-res model for the low-res
model. Both models were built and are run by the
same organization, contrary to what was
envisioned.
27Hierarchical Attrition Algorithms - ATCAL
- CONCEPT a set of equations is used to compute
attrition in a low-res model if a set of input
parameters are known (provided by a medium-res
model). The same set of equations can be used
"backwards" when the medium-res model is run to
generate the parameters it will provide in
accordance with its attrition results. - For each scenario which the low-res model needs,
the medium-res model is run in nine different
"vignettes", or shorter, narrower-scope scenarios
which fit with the larger scenario. These nine
vignettes vary the posture of the two opposing
sides and calculate results for each - Blue attack, Red prepared defense
- Blue attack, Red hasty defense
- Blue attack, Red delay
- Meeting engagement
- Static
- Red attack, Blue delay
- Red attack, Blue prep defense
- Red attack, Blue hasty defense
- Reserve
28Hierarchical Attrition Algorithms - ATCAL
- Medium-resolution model generates three
parameters (for point fire) - Pij Probability of kill of target j by firer i
- Aij Availability of target j to firer i
- RATEi shots per unit time by firer i
- Care must be taken to ensure that all Blue firer
types have an opportunity to fire at all Red
target types and vice versa, so that all Pij and
Aij have values.