Complexity Theory and Network Centric Warfare

Abstract : 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. Warfare is a complex system that is linked and interacts (in a coevolving way) with the surrounding socioeconomical and political context. Forgetting that war and warfare are an intimate part of a much larger complex system will lead to incomplete and even dangerously incorrect conclusions. Applying the approach of Complexity Theory to warfare leads one to the self-consistent realisation that warfare will have to be analysed in its larger context. Further work will need to examine how coevolution across the entire network of military, socioeconomical, and political interactions leads firstly to emergent effects at higher levels, and of equal importance how such effects lead to coevolution at the higher level. It will also be important to consider the robustness of such networks, and their vulnerability to damage.

[1]  D. Teichroew,et al.  Optimal control of dynamic operations research models , 1969 .

[2]  Kenneth Crewdson Bowen,et al.  Research Games: An Approach to the Study of Decision Processes , 1978 .

[3]  Andrew Ilachinski,et al.  Irreducible Semi-Autonomous Adaptive Combat (ISAAC): An Artificial-Life Approach to Land Warfare. , 1997 .

[4]  Roy E. Plotnick Fractals and Chaos in Geology and Geophysics , 1994 .

[5]  Michael K. Lauren,et al.  MAP-AWARE NON-UNIFORM AUTOMATA ( MANA ) — A NEW ZEALAND APPROACH TO SCENARIO MODELLING , 2003 .

[6]  M K Lauren Firepower concentration in cellular automaton combat models—an alternative to Lanchester , 2002, J. Oper. Res. Soc..

[7]  David Cohen All the world's a net , 2002 .

[8]  David S Alberts,et al.  Network Centric Warfare: Developing and Leveraging Information Superiority , 1999 .

[9]  N. Goldenfeld Lectures On Phase Transitions And The Renormalization Group , 1972 .

[10]  J. Sethna,et al.  Crackling noise , 2001, Nature.

[11]  Henry Stark,et al.  Probability, Random Processes, and Estimation Theory for Engineers , 1995 .

[12]  Jerome Bracken,et al.  Measurements of Effectiveness for the Information-Age Navy: The Effects of Network-Centric Operations on Combat Outcomes , 2002 .

[13]  Michael K. Lauren,et al.  Modelling Combat Using Fractals and the Statistics of Scaling Systems , 2000 .

[14]  D. Rowland The Effect of Combat Degradation on the Urban Battle , 1991 .

[15]  W. H. Zurek Complexity, Entropy and the Physics of Information , 1990 .

[16]  Michael K. Lauren,et al.  FRACTALS AND COMBAT MODELING: USING MANA TO EXPLORE THE ROLE OF ENTROPY IN COMPLEXITY SCIENCE , 2002 .

[17]  J. Meditch,et al.  Applied optimal control , 1972, IEEE Transactions on Automatic Control.

[18]  John Gordon,et al.  Measures of Effectiveness for the Information-Age Army , 2001 .

[19]  J Moffat,et al.  Measuring the effects of knowledge in military campaigns , 1997 .

[20]  Richard E. Blahut,et al.  Principles and practice of information theory , 1987 .

[21]  Melvin Dresher,et al.  A Game Theory Analysis of Tactical Air War , 1959 .

[22]  J. Sutherland The Quark and the Jaguar , 1994 .

[23]  I. Prigogine,et al.  From Being to Becoming: Time and Complexity in the Physical Sciences , 1982 .

[24]  D. Turcotte,et al.  Fractality and Self-Organized Criticality of Wars , 1998 .