This is a third paper in a cycle on distributed swarms, OODA loops and stigmergy co-authored with a PhD student of mine. The paper is titled Distributed Swarming and Stigmergic Effects on ISIS Networks: OODA Loop Model, and was published in the Journal of Media and Information Warfare. This is probably the densest and most interesting paper in the series, as we analyse information warfare waged by distributed swarms in the context of network-centric warfare theory, stigmergic adaptation, and John Boyd’s work on the OODA loop concept. For me the most interesting elements of the paper involve our discussion of Von Moltke’s concept of auftragstactic in the context of maneuver warfare in the information domain.
Tag: information warfare
These are some loosely organized observations about the nature of network topologies in the wild.
In terms of both agency and information, all entities, be they singular [person], plural [clan/tribe/small company], or meta-plural [nation/empire/global corporation] are essentially stacks of various network topologies. To understand how the entities operate in space these topologies can be simplified to a set of basic characteristics. When networks are mapped and discussed, it is usually at this 2-dimensional level. However, in addition to operating in space, all entities have to perform themselves in time.
This performative aspect of networks is harder to grasp, as it involves a continuously looping process of encountering other networks and adapting to them. In the process of performative adaptation all networks experience dynamic changes to their topologies, which in turn challenge their internal coherence. This process is fractal, in that at any one moment there is a vast multiplicity of networks interacting with each other across the entire surface of their periphery [important qualification here – fully distributed networks are all periphery]. There are several important aspects to this process, which for simplicity’s sake can be reduced to an interaction of two networks and classified as follows:
1] the topology of the network we are observing [A];
2] the topology of network B, that A is in the process of encountering;
3] the nature of the encounter: positive [dynamic collaboration], negative [dynamic war], zero sum [dynamic equilibrium].
All encounters are dynamic, and can collapse into each other at any moment. All encounters are also expressed in terms of entropy – they increase or decrease it within the network. Centralized networks cannot manage entropy very well and are extremely fragile to it.
Positive encounters are self explanatory, in that they allow networks to operate in a quasi-symbiotic relationship strengthening each network. These encounters are dynamically negentropic for both networks, in that they enable both networks to increase coherence and reduce entropy.
Negative encounters can be offensive or defensive, whereby one or both [or multiple] networks attempt to undermine and/or disrupt the internal coherency of the other network/s. These encounters are by definition entropic for at least one of the networks involved [often for all], in that they dramatically increase entropy in at least one of the combatants. They can however be negentropic for some of the participants. For example, WW2 was arguably negentropic for the US and highly entropic for European states.
Zero sum encounters are interesting, in that they represent a dynamic cancelling out of networks. There is neither cooperation nor war, but a state of co-presence without an exchange of entropy in a dynamic time-space range. I believe this is a rare type of encounters, because the absence of entropy exchange can appear only if 1] there is no exchange of information or agency, or 2] the amount of agency/information exchanged is identical from both sides. Needless to say, this process cannot be easily stabilized over a long time period and either morphs into one of the other two states or the networks stop encountering each other.