Discrete Dynamical Networks and Their Attractor Basins
Andrew Wuensche · 1998
A key notion in the study of network dynamics is that state-space is connected into basins of attraction. Convergence in attractor basins correlates with order-complexity-chaos measures on space-time patterns. A network's \\memory", its ability to categorize, is provided by the con- guration of its separate basins, trees and sub-trees. Based on computer simulations using the software Discrete Dynamics Lab[19], this paper provides an overview of recent work describing some of the issues, methods, measures, results, applications and conjectures. 1 Introduction Processes consisting of concurrent networks of interacting elements which aect each other's state over time are central to a wide range of natural and articial systems drawn from many areas of science; from physics to biology to cognition; to social and economic organization; to computation and articial life; to complex systems in general. The dynamics of these \\decision making" networks depends on the connections and update lo...