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C2 - Command and Control
AO - Area of Operations
xi For the last couple of decades, attempts have been made to develop some general understanding, and ultimately a theory, of systems that consist of many interacting components and many hierarchical layers. It is common to call these systems complex because it is impossible to reduce the overall behaviour of the system to a set of properties characterising the individual components. Interaction is able to produce properties at the collective level that are simply not present when the components are considered individually.
xii the ecological function emerges first when the different components are brought together and interaction is taken into account.
xii Another important feature of complex systems is their sensitivity to even small perturbations. The same action is found to lead to a very broad range of responses, making it exceedingly difficult to perform prediction or to develop any type of experience of a “typical scenario.” This must necessarily lead to great caution: do not expect what worked last time to work this time. The situation is exacerbated since real systems (ecological or social) undergo adaptation. This implies that the response to a given strategy most likely makes that strategy redundant... That complex systems adapt and change their properties fundamentally as a result of the intrinsic dynamics of the system is clearly extremely important.
xiii complex systems cannot be studied independently of their surroundings. Understanding the behaviour of a complex system necessitates a simultaneous understanding of the environment of the system.
xiii we see that it is vitally important to consider warfare as a complex system that is linked and interacts (in a coevolving way) with the surrounding socioeconomical and political context.
p.2 Complexity explains why interventions may have unanticipated consequences, but also explains how combat effects follow from these consequences. The intricate interrelationships of elements within a complex system give rise to multiple chains of dependencies. Change happens in the context of this intricate intertwining at all scales... before change at a macro level can be seen, it is taking place at many micro levels simultaneously. Hence, microcomponent interaction and change leads to macrosystem evolution.
p.3 One effect of the human element in conflict situations is to bring a degree of complexity into the situation such that the emergent behaviour of the system as a whole is extremely difficult to predict from the characteristics and relationships of the system elements.
p.42-43 From our analysis of these open and dissipative systems, it is clear that there are a number of key properties of complexity that are important to our consideration of the nature of future warfare. Such futures, involving the exploitation of loosely coupled command systems such as Network Centric Warfare, will have to take account of these key properties... 1. Nonlinerar Interaction... 2. Decentralised Control... 3. Self-Organisation... 4. Nonequilibrium Order... 5. Adaptation... 6. Collectivist Dynamics: the ability of elements to locally influence each other, and for the effects to ripple through the system, allows continual feedback between the evolving states of the elements of the system.
p.46 Combat is, by its nature, a complex activity.
p.46 Ashby's Law of Requisite Variety... indicates that to properly control such a system, the variety of the controller (the number of accessible states which it can occupy) must match the variety of the combat system itself. The control system itself, in other words, has to be complex... The essential idea is that a number of interacting units, behaving under small numbers of simple rules or algorithms, can generate extremely complex behaviour, corresponding to an extremely large number of accessible states, or a high variety configuration, in Cybernetic terms. It follows that, if we choose these simple interactions carefully, the resultant representation of C2 will be sufficient to control, in an acceptable way, the underlying combat model.
p.46-47 we need to ensure that the potentially chaotic behaviour generated by the interaction of these simple rules is 'damped' by a top-down C2 structure which remains focused on the overall, high-level, campaign objectives.
p.48-49 within a broad intent and constraints available to all the forces, the local force units self-synchronize under mission command in order to achieve the overall intent.
This process is enabled by the ability of the forces involved to robustly network. We can describe such a system as loosely coupled to capture the local freedom available to the units to prosecute their mission within an awareness of the overall intent and constraints imposed by high-level command.
p.50 Plexus means braided or entwined, from which is derived complexus, meaning braided together, and the English word complex is derived from the Latin. Complexity is therefore associated with the intricate intertwining or inter-connectivity of elements within a system and between a system and its environment.
p.50-51 The term complexity is used to refer to the theories of complexity as applied to complex adaptive systems (CAS). These are dynamic systems able to adapt and change within, or as part of, a changing environment. It is important to note, however, that there is no dichotomy between a system and its environment in the sense that a system always adapts to a changing environment. The notion to be explored is rather that of a system closely linked with all other related systems making up an "ecosystem." Within such a context, change needs to be seen in terms of coevolution with all other related systems... rather than as adaptation to a separate and distinct environment.
p.51 a complex system... exhibits nonlinear, emergent, adaptive behaviour. Nonlinear behaviour is associated with far-from-equilibrium, open systems, in that cause and effect are no longer linearly connected. This is ultimately due to the type of internal-external system interactions (feedback) affecting the system.
p.51 Enabling self-organisation can often be a source of innovation.
p.52 In systems where the dynamical evolution is a struggle against various types of thresholds or barriers, the action will predominantly occur where the net barrier to change is smallest... In the model ecosystem, the system self-organises towards a critical point where it has the greatest dynamical freedom... one of the key tenets of manoeuvre warfare - namely, to focus your strength against your enemy's weakness.
p.77 Understanding the behaviour of agent-based simulation models of conflict is now becoming more important, especially as... the agents gain intelligence and try to outsmart each other, producing potentially very complex behaviour.
p.85-87 Looking now at the phenomenon of control of the battlespace... We assume that the commander aims to establish control in this area. Firstly we have to define what this means... In discussion with senior UK commanders who have had recent operational experience at a high level, the concept of control of an area as corresponding to the prevention of flow through an area (flow in terms of an opposing force...) has been endorsed as a good analogy. We thus define the commander as having "weak control" of his area of operations if he can to some extent control movement through the AO.
p.90 it is easier to iterate towards good weak control than towards good strong control, as we would expect (since weak control is easier to achieve than strong control).
p.91 From a game theory perspective, we can see that each side is trying to drive its own value of control up, and the other side's down.
p.94 [Roske] "In a classic command post exercise, we inject human decisionmaking into a structured environment to generate open system behaviours. Human decisionmaking represents energy crossing the structured system boundary..."
p.95 There are three major problems with the use of wargames to support military studies: (1) too little output data, (2) the likelihood of atypical results, and (3) oversimplification. The first problem stems from the fact that wargames are generally slow, cumbersome, and resource intensive. Consequently, most analysts who use them to support studies plan only a small number of games, thus precluding significant statistical results. The second problem recognises the possibility that the sequence of decisions taken by the players in these games represents statistical outliers. Players may adopt extreme strategies that exist "outside" of what is considered to be a typical military response. The third problem reflects the fact that human players can only approximate the results of combat operations. In our studies, we addressed these problems in three ways: by arguing that our wargames are quasi-memoryless processes for tactical situation assessment; by introducing the epitomising strategy principle in wargames; and by embedding computer models to adjudicate engagements in the manual games. [JLJ - perhaps this represents our "evaluation function" of the "typical" consequences]
p.96 A dynamic process is said to be memoryless or Markovian if at each cycle, the state of the system is influenced only by the state of the system in the previous cycle, and not by the specific history of the system (Stark and Woods [13]).
p.104 Given the complexity of the two-sided optimal control construct for the wargames, we forego attempts to apply any closed form solution and rely instead on the replication of instances of the game from each of the scenarios and for the several cases to be examined. Even this however can be extremely time consuming
p.106 What remains to be defined is a utility function that is some measure of how well both sides accomplish their mission.
p.130 there appears to be a point where the knowledge available to the commander exceeds his capacity to act on it
p.148-149 We started by considering what we can learn from natural systems: an ecosystem in which species coevolve locally; a fluid forming an interface when it is pinned; the effect of forest fires. All of these show regularities and emergent behaviours of the whole system that can be captured and deduced using mathematical models. We have also shown how the same ideas of local coevolution within such "open" systems are very relevant to thinking about the consequences of a network-centric form of warfare, where units coevolve (self-synchronise) across an information grid. By exploiting this linkage, it is possible to build quantitative models that help us to understand the likely emergent behaviour of such coevolving networks of force interaction.
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