Analytical and Conceptual
Frameworks for Automated Scenario Generation:
Application to Tactical Theater
Air Warfare
©1989, 2000 Vista Research
Corporation. All rights reserved.
I. Conceptual Framework
A. Definitions
This appendix describes conceptual and analytical frameworks for
developing an automated methodology for generation of scenarios. The term "conceptual framework"
refers to a description of the general concepts underlying our approach. The term "analytical framework"
refers to a quantification of the conceptual framework, in terms of specific
variables, functions, and procedures.
In this report, the term "scenario" is used to refer
to a description of the initial compositions of the opposing forces, the
targets, and the battle plan. In order
to develop a battle plan, the opposing forces develop strategies and
tactics. The term "strategy"
refers to a probability distribution defined over a set of high-echelon
(theater-level) actions or decisions (employment of task forces or force units
at division or higher level). The term
"tactic" refers to a probability distribution defined over a set of
low-echelon actions or decisions (employment of units or weapons at the
division level or below). (In air
warfare, the term "tactical" refers to air attack in close support of
friendly ground forces.) A
"plan" is a particular sample from a strategy or tactic, i.e., a
specified military action or decision, selected according to the probabilities
that define the strategy or tactic.
The preceding definitions of "strategy" and
"tactic" are military usages of these terms. In the terminology of statistical decision
theory, there is no consideration of echelon, and both concepts would be
referred to using the term "strategy" (i.e., a probability
distribution defined over a set of actions or decisions).
In order to generate a scenario, it is necessary to specify the
force levels and targets prior to battle, to determine a strategy (or tactic)
for the employment of the forces, and to select a specific plan from that
strategy (or tactic). At the strategic
(theater) level, a scenario could involve simply the specification of an
initial state of the forces and a strategic plan. At a tactical level, a scenario would include
specification of the initial state of the forces, a strategic plan for the
high-echelon forces, and tactical plans for the lower-echelon forces.
In addition to the military concepts of strategy and tactic,
there is a third level of military planning, viz., "operational
art." "Strategy" refers
to the theater echelon level; "tactic" refers to division or
lower-echelon; "operational art" refers to the army/front echelon
levels. The concept of operational art
is relevant to AirLand Battle doctrine, which is
concerned with the rapid, synchronized movement, concentration and application
of large military units.
The generation of a scenario involves the specification of the
initial compositions of the forces, the targets, the combat goals of the two
sides, the generation of strategies and tactics to achieve those goals, and the
sampling of battle plans from those strategies and tactics. Hence, although the term "scenario"
refers simply to a specification of the initial state of the forces and the battle
plan, the task of developing an automated scenario generation system includes
the tasks of developing automated strategy, tactic, and plan generation
systems. The term "scenario
generation," as used in this report, could reasonably be described by the
terms "war plan generator" or "battle plan generator."
B. Motivation for an Automated Scenario Generation System
The conceptual framework for the proposed approach is derived
from a consideration of why an automated scenario generation capability is
needed. Such a capability is needed to
generate probability samples of scenarios for use in test and evaluation of
military concepts and systems. Because
of the high cost of developing scenarios by manual means, many military systems
evaluations are based on just one or a very limited number of scenarios. Moreover, the scenario generation process
often takes place without reference to a well-defined probability space (i.e, a well-defined population of scenarios and a
probability distribution for selecting members from that population).
Typically, the scenario generation process is
"nonparametric." By the term
"nonparametric" is meant that a scenario is specified in detail
without reference to parametrically specified probability distributions. While the use of nonparametric procedures for
specifying scenarios may be cumbersome, it is not the most serious problem,
from a methodological point of view. A
more serious problem associated with many scenario generation procedures is
that they make no reference to a sample space or probability sampling. In statistical terminology, the developed
scenarios constitute a "judgment" sample. The problem with judgment sampling is that,
while everyone may agree that it is reasonable, the methods of statistical
inference cannot be used to make inferences from the sample about a larger
population of scenarios, based on the sample results.
In summary, there are two major problems associated with the use
of manual methods for scenario generation.
The first problem is the fact that the high cost of manually generating
scenarios means that few of them can be used in an evaluation, thereby
restricting both the reliability (precision) and the scope of inference of
performance evaluations based on those scenarios. The second problem -- a methodological one --
is that the procedures used to manually generate scenarios typically preclude
the legitimate application of statistical analysis procedures to make
broad-scope inferences from analyses based on the scenarios, since the
probability space underlying the scenario selection is not well-defined. To reiterate, the difficulty with
"judgment" or "consensus" scenarios, then, is that, because
no well-defined population of scenarios is identified, and because no
well-defined probability sampling method is used to select the scenario from an
identified population, the methods of statistics cannot legitimately be used to
infer the performance estimates associated with the scenario to a well-defined
large population extending beyond the scenarios actually used in the
evaluation.
C. Goal of the Project
The goal in the proposed study is to develop a means for
parametrically defining a population of scenarios, and a rapid means for
selecting probability samples from that population. Such a capability could be used to provide
samples of scenarios for evaluation studies, and those studies could then infer
the results from the sampled scenarios to the larger scenario population. The basis of inference would be firm, and the
scope of inference would be broad. The
availability of a rapid means of scenario generation would enable statistical
experimental design and sample survey procedures to be applied to the scenario
selection process. The inference methods
of statistics could then legitimately be applied to the analysis of the data
obtained from the sampled scenarios.
The conceptual basis proposed for a scenario generation system
is to specify a mathematical representation, or model, of combat; to use that
model as a basis for specifying a population of scenarios; and to specify a
method for selecting probability samples from that population.
D. Concept of
The preceding paragraphs have described the general concept of a
scenario. Prior to defining an
analytical framework for scenario generation, we shall define some additional warfare
concepts. The analytical framework that
follows quantifies these concepts (i.e., both the scenario generation concepts
and the additional warfare concepts).
First, we describe the major elements of tactical air combat
(either actual or modelled). The major steps of the process are the
following:
1. Define Force Elements and Targets
o Define offensive weapon types
(in tactical theater air warfare, aircraft or aircraft force mixes)
o Define defensive weapon types
(interceptors, either aircraft, artillery or missiles)
o Define targets (specification
of value and vulnerability; vulnerability is specified by a damage function
that specifies expected damage (probability that target is destroyed, or
expected proportion of value destroyed, as a function of the weapons and
interceptors allocated to the target))
o Define force units, task
forces
In tactical theater air warfare, the term
"weapon" would typically refer to an aircraft type, rather than a
specific store (bomb, missile) carried by an aircraft. The term "target" may refer to a
force element (weapon, interceptor) or item of intrinsic value (targets of
intrinsic value include civilian population, agricultural territory,
infrastructure elements, and industry).
2. Specify Constraints
o Resource Constraints
o Numbers of weapons of each type
o Numbers of interceptors of each type
o Numbers of targets and characteristics (value and damage
function parameters)
o Other Constraints
o Physical constraints (rates, ranges, flyout
radii, mission durations)
o Organizational constraints
o Environmental constraints (e.g., corridors, terrain, weather, day/night)
o Logistic constraints (e.g., POL, ammunition)
o Political constraints
o Conditions under which certain targets will or will not be
attacked
o Military doctrine
3. Specify Combat Goals
o Specify combat goals in terms
of observable, quantifiable measures of the degree of success in achieving
combat objectives, such as the following:
o Enemy targets destroyed
o Friendly targets saved
o The combat goals may be
specified in terms of the maximization or minimization of an objective
function, or the occurrence of a specified set of conditions
4. Determine Strategies/Tactics
o Determine strategies
(probabilistic specification of the use of task forces or major units), in
accordance with stated combat goals and doctrine
o Determine tactics
(probabilistic specification of the use of units or weapons), in accordance
with stated goals and doctrine
5. Generate
o Select a sample from the strategy
and tactic distributions. (The strategy
or tactic is a probability distribution over a set of military actions or
decisions, such as the allocation of a number of weapons and interceptors to a
set of targets. The battle plan is a
specific set of decisions or actions sampled in accordance with this
probability distribution.)
6. Execute Plan and Assess Results
o Conduct (or simulate) the
battle, using the plan
o Evaluate objective function or
note occurrence of conditions corresponding to goal achievement
7. Describe Scenario
o The scenario is defined by the
initial state of the forces and targets, and the battle plan, i.e., by items 1,
2, and 5 of this list. It is described
by:
o Positioning of units (offensive, defensive)
o Engagements of units
o Assignment of aircraft to missions
o Assignment of aircraft to targets
o Allocation of interceptors to targets
Note that the scenario description corresponds to the end result
of steps 1-5. It is the description of
the initial state of the forces and the battle plan, but does not include the
battle outcome. The scenario description
need not (but may) include explicit description of the battle goals, strategy,
and tactics, which are reflected in the battle plan. That is, although the generation of a
scenario involves the generation of strategies, tactics, and plans, a
description of a generated scenario need not include a description of the
strategies and tactics developed and used to generate it.
Strategy Specification.
A critical aspect of the conceptual framework is the means for
determining the strategies and tactics (step 4, above). We propose that the conceptual framework
include the use of ”optimal strategies and tactics”,
i.e., the strategies/tactics that achieve a stated combat goal. It is noted that not all military analysts
agree that the use of optimal strategies is important, or even desirable. For example, some major wargame
models (e.g., VECTOR II, VIC) utilize tactical decision rules derived from the
judgment and experience of military experts, rather than optimal strategies.
We do not dismiss the importance of judgment strategies in
certain applications, such as training and scenario evaluation. In fact, actual wars are fought using
judgment strategies. We believe,
however, that it is preferable to employ optimal strategies rather than
judgment strategies as the basis for automated scenario generation, for several
reasons. First, this approach
acknowledges, accepts, and uses the science and methodology of statistical
decision theory as the basis for evaluation.
This approach is easy to defend.
In evaluating a system, it seems reasonable to examine the system
performance in a context in which both the offense and defense are operating in
the best possible (optimal) fashion consistent with stated combat goals (even
though it may be also of interest to examine system performance under suboptimal conditions).
Second, corresponding to the class of optimal strategies is a
well-defined population of scenarios; viz., the population of scenarios
corresponding to optimal strategies. The
population of scenarios corresponding to judgment strategies is not well
defined. Third, the use of optimal
strategies lends itself to speed, which is essential for an automated scenario
generation system. While the use of
judgment strategies may have a role in training and detailed wargaming, and in scenario assessment, it is not considered
a good candidate for fast, automatic generation of many scenarios, or of
scenarios having specified properties.
II. Analytical Framework
The following paragraphs present an analytical framework for
combat, including air, land, and sea forces.
The analytical framework that follows quantifies the concepts presented
in the preceding paragraphs. The
presentation that follows is in general terms, i.e., it applies to any type of
warfare (land, air, or sea). In a
particular application, not all of the structure that is defined below may
apply, or be utilized (e.g., an aircraft mission analyst may choose not to
become involved with the definition of task forces, but prefer to conduct an
analysis simply in terms of total numbers of weapons and interceptors).
In quantitative terms, the analytical framework for the model is
as follows. First, we define a number of ”task forces”
(comprised of military units). A
task force (Xi) =
(x1,x2,...,xn), is comprised of various
”units” (e.g., in tactical theater air warfare, force mixes of aircraft), xj = (xj1,xj2,...,xjm), which are
in turn comprised of various ”force elements” (e.g., in tactical theater air
warfare, aircraft), xjk, which may be separately
targeted, and the failure, neutralization, or destruction of which can affect
the performance of the unit. These force
elements include weapons (both destructive, such as artillery, and disruptive,
such as EW or misinformation), command and control centers, communications
equipment, intelligence sensors, supplies, and personnel.
One or more task forces may be assigned to a ”task-force
mission”, which is defined in terms of the assignment of the task forces
against another task force. A ”unit mission” is the assignment of units against other
units, or against targets. One or more
weapons of a task force may be assigned a ”weapon
mission”, which is defined in terms of the assignment of the weapons against a
target (force element, either weapon or nonweapon, or
target of intrinsic value).
A ”battle strategy” is a set of
probabilities, ”pi, that specify the likelihood that a task force will be
assigned to a particular mission. A ”tactic” is a set of probabilities, pijk,
that specify the likelihood that a weapon will be assigned against a force
element.
A ”plan” (or battle plan) is a
particular sample assignment, selected according to the probabilities specified
by a strategy or tactic. In particular, a ”strategic plan” is a sample from a strategy, and a
”tactical plan” is a sample from a tactic.
A ”scenario” is a description of
the force initial state (prior to battle) and a battle plan. This description does not include a description
of the results (outcome) of executing that plan. The battle outcome is a random
variable; because of stochastic variability, the same battle plan could realize
many different outcomes. The battle
outcome is determined by executing the plan in a real battle, or by inputting
the scenario to a war-game (combat) simulation model.
A ”battle”, then, is the
implementation of a battle plan -- the execution by task forces and units of
their assigned missions, and the execution by weapons of their assigned missions. The term "battle" refers to all of
the events that occur during the course of executing the battle plan.
The ”battle outcome” is a
quantitative description of the result of the battle. The term "battle outcome" may be
used to refer to a description of the battle at a series of points in time, or
at a single point in time (the "end" of the battle), at which
hostilities cease. It may be expressed
in terms of the expected damage, or in terms of functions related to expected
damage.
The expected damage is determined using damage functions, which
specify the probability of destruction or neutralization of each target, or the
expected proportion of the target value destroyed, given the interaction of the
forces of the two sides:
dPxPy = D(X,Y,Px,Py)
where X symbolically denotes all of the task forces, units, and
force elements of the friendly side (side 1, side A, the Blue side), Y
symbolically denotes all of the task forces, units, and force elements of the
enemy side (side 2, side B, the Red side), Px denotes
a side 1 strategy (i.e., the probabilities of assignment of the friendly side
task forces, units, and force elements to missions), and Py
denotes a side 2 strategy (i.e., the probabilities of assignment of the enemy
side task forces, units, and force elements to missions).
During the course of determining a specific strategy or tactic
(i.e., Px and Py), the force levels X and Y are considered fixed.
As mentioned, the battle outcome may be expressed in terms of
the losses of each type of force element, unit, or target of intrinsic
value. Alternatively, discrete loss or
victory indicator variables may be defined in terms of a set of logical
statements about the magnitudes of losses of each force element, unit, or other
target (just as goals are defined). For
each side, a set of payoff functions, Hx and Hy, are defined -- one for each goal statement. The payoff is a function of the damage.
A ”war” is a sequence of
battles. After each battle, the
remaining forces are reconstituted to the extent that remaining force elements
permit (recall that supplies, ammunition, payloads are force elements). A ”war strategy” is
a scheme for determining a sequence of battle strategies.
”Goal Specification”. The goals are specified by the
user, in terms of quantitative criteria associated with battle outcome. A goal may be specified in terms of expected
damage to various types of force elements, territorial losses, personnel
losses, target damage, or other measurable quantities functionally related to
expected damage.
”Constraint Specification”. Constraints include:
o Resource constraints (weapon, interceptor stockpiles)
o Physical constraints
o Organizational constraints
o Environmental constraints
o Logistic constraints
o Movement constraints
o Strategic and tactical constraints
o Political constraints
o Military doctrine constraints