7:00 – 4:30 ASRC GEOS

- Still looking at what’s wrong with my NK model. I found Random Boolean Networks, when looking for “random binary networks kauffman example“. It also has a bibliography that looks helpful as well
- Introduction to Random Boolean Networks
*The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic. The tutorial, intended for a broad audience, presents the state of the art in RBNs, spanning over several lines of research carried out by different groups. We focus on research done within artificial life, as we cannot exhaust the abundant research done over the decades related to RBNs.*- I can add a display that shows this:
- Got that working
- Rewrote so that there is an evolve without a fitness test. Trying to set up transition patterns like this:
- The thing is, I don’t see how the K part works here…
- I think I got it working!

- Complex and Adaptive Dynamical Systems: A Primer
*An thorough introduction is given at an introductory level to the field of quantitative complex system science, with special emphasis on emergence in dynamical systems based on network topologies. Subjects treated include graph theory and small-world networks, a generic introduction to the concepts of dynamical system theory, random Boolean networks, cellular automata and self-organized criticality, the statistical modeling of Darwinian evolution, synchronization phenomena and an introduction to the theory of cognitive systems.*

*It inludes chapter on Graph Theory and Small-World Networks, Chaos, Bifurcations and Diffusion, Complexity and Information Theory, Random Boolean Networks, Cellular Automata and Self-Organized Criticality, Darwinian evolution, Hypercycles and Game Theory, Synchronization Phenomena and Elements of Cognitive System Theory.*

- Introduction to Random Boolean Networks