Notes

Chapter 6: Starting from Randomness


Section 7: The Notion of Attractors

2D generalizations [of entropies] [Attractors in] discrete systems Attractors in systems based on numbers Attractors in Turing machines [Cellular automaton state] network properties Cycles and zeta functions Entropies and dimensions [in cellular automata] Entropy estimates Excluded blocks [in cellular automaton evolution] Finite automata Generating functions [for regular languages] History [of dynamical systems approaches] History [of finite automata] Implementation [of cellular automaton state networks] Iterated maps Nested structure of attractors Probability-based entropies [Properties of] random networks Regular expressions Regular languages Spacetime patches [in cellular automata] [State networks for] additive rules [State networks for] shift rules [State networks for] systems of limited size Surjectivity and injectivity [of cellular automaton maps] Symmetries [and state networks] Temporal sequences [in cellular automata]

From Stephen Wolfram: A New Kind of Science [citation]