diff --git a/cellular_automata/elementary_cellular_automaton.py b/cellular_automata/elementary_cellular_automaton.py
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+"""
+Elementary Cellular Automaton - Rule 30
+---------------------------------------
+
+A one-dimensional cellular automaton introduced by Stephen Wolfram.
+Each cell's next state depends on its current state and its two immediate neighbors.
+
+Reference:
+    https://en.wikipedia.org/wiki/Rule_30
+"""
+
+
+def rule_30_step(current: list[int]) -> list[int]:
+    """
+    Compute the next generation of a one-dimensional cellular automaton
+    following Wolfram's Rule 30.
+
+    Each cell's next state is determined by its left, center, and right neighbors.
+
+    Args:
+        current (list[int]): The current generation as a list of 0s (dead)
+            and 1s (alive).
+
+    Returns:
+        list[int]: The next generation as a list of 0s and 1s.
+
+    Example:
+        >>> rule_30_step([0, 0, 1, 0, 0])
+        [0, 1, 1, 1, 0]
+    """
+    next_gen = []
+    for i in range(len(current)):
+        left = current[i - 1] if i > 0 else 0
+        center = current[i]
+        right = current[i + 1] if i < len(current) - 1 else 0
+
+        # Combine neighbors into a 3-bit pattern
+        pattern = (left << 2) | (center << 1) | right
+
+        # Rule 30 binary: 00011110 (bitwise representation of 30)
+        next_gen.append((30 >> pattern) & 1)
+
+    return next_gen
+
+
+def generate_rule_30(size: int = 31, generations: int = 15) -> list[list[int]]:
+    """
+    Generate multiple generations of Rule 30 automaton.
+
+    Args:
+        size (int): Number of cells in one generation. Default is 31.
+        generations (int): Number of generations to evolve. Default is 15.
+
+    Returns:
+        list[list[int]]: A list of generations (each a list of 0s and 1s).
+
+    Example:
+        >>> len(generate_rule_30(15, 5))
+        5
+    """
+    grid = [[0] * size for _ in range(generations)]
+    grid[0][size // 2] = 1  # Start with a single live cell in the middle
+
+    for i in range(1, generations):
+        grid[i] = rule_30_step(grid[i - 1])
+
+    return grid
+
+
+if __name__ == "__main__":
+    # Run an example simulation
+    generations = generate_rule_30(31, 15)
+    for row in generations:
+        print("".join("█" if cell else " " for cell in row))