Adaptive Systems Design
Channel: Systems Innovation
Date: 23/12/2014

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Adaptation is the capacity for a system to respond and alter its state in response to so change within its environment, in this section of our course we discuss the dynamics of complex adaptive engineered systems and how to approach designing them.
Adaptation is the capacity of a system to alter its state in response to some event within its environment, this capacity of adaptation is something we more often associate with biological systems as apposed to the technologies we design. The industrial world we have engineered is in many ways a relatively static one, we produce things like electrical power grids, buildings and chairs and then they sit there, specifically designed not to change.
Every day we walk by the same advertisement on the street, it will present the same information to thousands of people that day but it will only be of any relevance to a very small percentage of them and because it is static they will only take note of it the first time before tuning it out to become simply background noise.
Now imagine if that advertisement changed every day, that is to say it was dynamic, instead of a poster we put in a screen that could be updated, it would be of more relevance, more functional. Now lets go even a step further, imagine if this screen could receive information about the profiles and preference of the users that were in its vicinity and dynamically deliver content relevant to their interests. This is the world of complex adaptive engineered systems and as information technology provides us with the tools for building smarter technologies it is increasingly the would we have to design for.
To understand this transition from static to adaptive systems lets take the history of the web as a good example. Web 1.0 was a very static systems where web developers hard coded web pages, when you visited a site the server just give you the same page that had been written possibly two or three years earlier with no changes. Web 2.0 that we all know and love leveraged new server side scripting technologies to get information in and out of databases and thus dynamically updating webpages making them interactive and change overtime. The emerging web 3.0 uses semantic technologies and social networking to adapt content relevant to your specific profile and interests, thus making it not just dynamic but also responsive to the context.
Out side of the web the massive cost reduction in integrated circuits is leading to sensors and actuators being placed in many devices and objects, as packages within supply changes, cars in traffic and electrical power grids are becoming smarter, they can respond to events within their local environment through realtime mesh networks.
But they can also feed data into large centralised systems for analysis, allowing for greater optimisation through dynamic load balancing, as things like washing machines and street lights begin to have the capacity to adapt their power demands to the current load on the system.
There are essentially two levels to these complex adaptive engineered systems that we need to consider, the micro and the macro.
On the micro level we need elements with some form of control system, a control system is a mechanism for taking in information, processing it according to some set of instructions and generation a response that alters the state of the component.
Of cause all living creatures have this, from the simplest single celled organisms to the most complex, the human brain. But increasingly we are using what we call cyber-physical systems to enable all kinds of technology to have this adaptive functionality as they become part of networks of technologies that can communicate and respond to the changes in state of other technologies in real time. As is the case in automated production lines, aircrafts and mass transit systems.
On the macro scale, when we are designing these adaptive systems we can no longer rigidly control the system and determine its functionality in the way we can when say designing a bridge, as the end result is going to be more organic, like an ecosystem of products, devices and people interacting and adapting within networks rather than the ridged mechanical systems we are used to.
So if we take away this key feature of control that is central to our tradition conception of being able to design, where we see constraining the autonomy of the components as a prerequisite to design, how then can we engineer these adaptive systems at all? The answer is to work with the innate features of adaptive systems not against them, that sounds nice, but what dose this mean exactly?


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