Adaptive Behaviour and Emergence
Description
Continuing advances in information and communications technology (ICT) are increasing the scale and connectivity of today's engineered systems. Managing the resultant complexity is becoming the central challenge for UK industry and government: from software, to cities and even stock exchanges. Across the UK, a wide range of internationally leading research groups are addressing this challenge. In many cases they draw inspiration from biology, which provides innumerable examples of systems that cope with complexity. From cells to ecosystems, biology achieves scalability, adaptability, self-repair, and robustness, often by exploiting "emergent" system-level behaviours. Achieving equivalent success in engineered systems is the root problem that we face.
In the first of our short courses, we introduce the core concepts of complexity in the context of both natural and engineered systems, and explore the ways in which new computational systems, models, and simulations are taking part in complexity science through a series of lectures and workshop activities.
| Slides | |
| 0:01 | Introduction to Complexity Science |
| 0:34 | Adaptive Complexity |
| 2:34 | Terms |
| 5:34 | Complex Adaptive Systems |
| 8:08 | Gaia |
| 10:10 | Fallacies, Misconceptions, etc. |
| 12:21 | Units of Selection |
| 16:24 | Group Selectionist Thought |
| 22:15 | Game Theory |
| 29:41 | Progress |
| 31:45 | Evolution ≠ Optimization |
| 36:20 | Arms Races |
| 45:33 | Major Transitions |
| 47:35 | Fitness Landscapes |
| 53:42 | “Open-Ended Evolution” |
| 56:45 | Apparent Design ≠ Evolution |
| 61:11 | Constraints vs. Opportunities |
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Nice zoom on the sleeping student at 39:00
Great content again, the video was a bit of a struggle in parts waiting for the video to catch up with itself.