Complex Systems CoP Complex System Engineering R. Abbott Corporate Chief Architect/Engineer Division (Rotation) 19 April 2007.

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Complex Systems CoP Complex System Engineering R. Abbott Corporate Chief Architect/Engineer Division (Rotation) 19 April 2007

Complex Systems Engineering Complex systems are no longer mysterious. We have a broad consensus about what we mean by a complex system, what their properties are, and how they operate. It’s time to put complex systems to work.

Characteristics – structure Multi-scalar, i.e., multiple levels of abstraction IT systems involve quantum physics, solid-state electronics, gates & logic, software (often many levels), CONOPs, … Prone to phase transitions/chaos: small change → big effect. Each level illustrates “emergence”—sometimes planned sometime not. But each level has a (physical) feasibility range. If the system involves real physical stuff … No useful bottom level. Quarks? Quantum waves? Strings? Hence no good models of evolutionary arms races — or for evolving or simulating geckos, which rely on the van der Waals force to climb. The levels cannot be completely isolated from each other … or we would have magic, i.e., new sources of causation, e.g., vitalism. except when implemented in software(!). But still have feasibility ranges.

Characteristics – group/environment Intimately entangled with its environment. Built to interact with its environment—to do something in the world. Must adapt to a continually changing environment The environment continually adapts to it. Can often be controlled/manipulated by modifying its environment. (Snake story) Simultaneously (a) deployed and (b) under development and self-repair, e.g., biological organisms, governments, corporation, Wikipedia. Each level of abstraction is often a multi-sided platform. A shopping center, an operating system, a browser, a standard. (Plug & play satellite.) Dynamic entities are real but not rigidly decomposable. (Chicken example). Must extract energy from its environment to persist. (“Far from equilibrium.”) Societies “agents;” not monolithic structures; system of systems. A new group leader selected, employees go home at night. Reductionist blind spot. Group entities exist even though they can be explained. Reductionism/decomposition not a good model. Components continually change. Requires a well thought out governance structure; the difference between a collection and a functioning organization. (Wilson, Evolution for Everyone.)

Innovative (internal) environments Structure & governance: the (within-group) environment as a commons, e.g., the free-market economic system, the web. (“DoD transformation”) Encourage individual action that benefits both the individual and the group at the expense of neither. Minimize overhead: bureaucracy, corruption, extortion, free-riders, … Minimize within-group conflict and cancers without stifling innovation. Decentralized but with some centralized authority. A reasonable level of stability and continuity. A means to change when needed. Governance requires individual decisions. How to mitigate problems caused by the inevitable conflicts of interest. Infrastructures/platforms: communication, transportation, money & banking, judicial, … Means to create new ones. How can a top-down command organization support bottom-up innovation? How can a leader emerge without rising through the ranks? Start a business, run for office, write a paper, … (What’s the military equivalent?) How can new products/services be created and installed? Anyone can create a web site, file a patent, … (What’s the military equivalent? DARPA.) How can energy aggregators emerge? (Top-down organizations are energy distributors.) How can (and when should) an organization that is funded top-down enable bottom-up energy allocation and aggregation, i.e. markets? (What’s the military equivalent?)

Our task – to put these ideas to work To refine, clarify, and formalize them. To evangelize. To make them intuitive, commonplace, and everyday— a part of everyone’s vernacular. To use them to conceptualize our systems. To make them operational. To adapt them to practice in building real systems. To create development processes based on them. To build tools that allow anyone to use them.