Notes

Chapter 6: Starting from Randomness


Section 1: The Emergence of Order

Continual injection of randomness [in cellular automata] History [of emergence of order] Properties of [initially random cellular automaton] patterns

Section 2: Four Classes of Behavior

2D class 4 cellular automata 3D class 4 [cellular automaton] rules Class 4 [cellular automaton] rules [Classes in] continuous cellular automata Different runs [of initially random cellular automata] Frequencies of [cellular automaton] classes Game of Life [cellular automaton] History [of cellular automaton classes] Nearby cellular automaton rules Random initial conditions in other systems States of matter [and cellular automaton classes] Subclasses within class 4 [Subset of] elementary rules Undecidability [of cellular automaton classes]

Section 3: Sensitivity to Initial Conditions

Difference patterns [in cellular automata] Lyapunov exponents Properties [of difference patterns]

Section 4: Systems of Limited Size and Class 2 Behavior

Additive cellular automata [in finite regions] Comparison of [periods for cellular automaton] rules Cyclic addition Cyclic multiplication Implementing boundary conditions [in cellular automata] Maximum periods [in cellular automata] [Periods in] rules 30 and 45

Section 5: Randomness in Class 3 Systems

Additive [cellular automaton] rules Densities in other [cellular automaton] rules Density in rule 90 Density oscillations in rule 73 Generalized additivity [in cellular automata] Probabilistic estimates [of cellular automaton properties] Rule 218 [with simple initial conditions] Rule 22 [with simple initial conditions] Rule 225 [with simple initial conditions] Rule 94 [with simple initial conditions]

Section 6: Special Initial Conditions

Fractal dimensions [of additive cellular automata] General associative [cellular automaton] rules Localized structures [in cellular automata] Nested initial conditions [in cellular automata] Nesting in rule 45 Renormalization group Repeating blocks [in cellular automata] [Repetition in] 2D cellular automata [Repetition in] systems based on numbers Rule emulations Sarkovskii's theorem Self-similarity of additive [cellular automaton] rules Square root of rule 30 Uniqueness of patterns [in cellular automata]

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]

Section 8: Structures in Class 4 Systems

Background [in rule 110] Collisions [in rule 110] Glider gun [in rule 110] [Structures in] other 2D cellular automata Structures [in rule 110] [Structures in] the Game of Life Structures in Turing machines Survival data [for initial conditions in code 20]

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