Cellular automata exhibit emergent behavior from simple rules from "summary" of Code by Charles Petzold
The behavior of cellular automata is fascinating because it emerges from rules that are astonishingly simple. These rules are typically a set of instructions that dictate how the cells in the automaton should evolve over time. Each cell follows the same rules based on its current state and the states of its neighboring cells. Despite the simplicity of these rules, complex and unexpected patterns can arise as the automaton evolves. The emergent behavior of cellular automata is a result of the interactions between individual cells following the same rules. As each cell updates its state based on its neighbors, patterns begin to form and propagate throughout the automaton. These patterns can exhibit characteristics such as replication, symmetry, and self-organization, all of which emerge from the basic rules governing each cell's behavior. One of the most famous examples of emergent behavior in cellular automata is Conway's Game of Life. In this simple two-dimensional automaton, cells can be in one of two states - alive or dead. The rules dictate how a cell's state should change based on the number of alive neighbors it has. Despite the simplicity of these rules, the Game of Life can produce an astonishing array of patterns, including gliders, oscillators, and even structures that can replicate themselves. The concept of emergent behavior in cellular automata highlights the power of simple rules to give rise to complex and unpredictable phenomena. By studying how these patterns emerge, we can gain insights into the underlying principles that govern complex systems in nature and society. The simplicity of the rules governing cellular automata belies the richness and diversity of behaviors that can arise, making them a powerful tool for exploring the dynamics of complex systems.
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