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Commit bd01867

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Cellular Automation Wars Script Added
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‎Cellular Automaton Wars/README.md‎

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# Cellular Automaton Wars
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Cellular Automaton Wars is a simulation game where players design and deploy cellular automaton-based organisms to compete for resources in a virtual environment. Each organism's behavior is determined by its cellular automaton rules, and the player must strategize to create the most successful organisms and outcompete others.
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## Features
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- Organisms interact with nearby cells and consume resources.
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- Organisms have energy levels and can reproduce when reaching a certain threshold.
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- Organisms can move left or right based on certain conditions or rules.
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- The player can influence the game by adding/removing organisms and resources at specific locations.
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## How to Use
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1. Clone the repository or download the script file.
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2. Open a terminal or command prompt and navigate to the directory containing the script.
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3. Run the script using Python:
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```bash
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python cellular_automaton_wars.py
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```
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4. The script will initialize the grid with organisms and resources and simulate their behavior for a certain number of iterations. The output will display the state of the grid at each iteration.
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## Customization
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You can customize the game by adjusting the following constants in the script:
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- `GRID_SIZE`: Change the size of the grid to accommodate more cells.
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- `NUM_ORGANISMS`: Set the initial number of organisms in the grid.
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- `NUM_RESOURCES`: Set the initial number of resources in the grid.
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- `ENERGY_THRESHOLD`: Adjust the energy threshold for organisms to reproduce.
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You can also define new rules in the `RULES` dictionary to create different behaviors for organisms based on their energy levels.
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## Contributions
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Contributions are welcome! If you find any issues or have ideas to improve the game, please feel free to create a pull request or open an issue.
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## Acknowledgments
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The game is inspired by cellular automaton simulations and evolutionary algorithms.
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import random
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GRID_SIZE = 50
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NUM_ORGANISMS = 5
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NUM_RESOURCES = 20
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ENERGY_THRESHOLD = 10
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RULES = {
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0: lambda neighbors, energy: (sum(neighbors) + energy) % 2,
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1: lambda neighbors, energy: (sum(neighbors) - energy) % 2
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}
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def initialize_grid():
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grid = [0] * GRID_SIZE
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for _ in range(NUM_ORGANISMS):
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organism_position = random.randint(0, GRID_SIZE - 1)
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grid[organism_position] = random.randint(1, 5)
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for _ in range(NUM_RESOURCES):
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resource_position = random.randint(0, GRID_SIZE - 1)
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resource_value = random.randint(1, 5)
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grid[resource_position] = -resource_value
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return grid
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def get_neighbors(grid, index):
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neighbors = []
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if index > 0:
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neighbors.append(grid[index - 1])
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if index < GRID_SIZE - 1:
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neighbors.append(grid[index + 1])
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return neighbors
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def apply_rule(grid, index):
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cell_state = grid[index]
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neighbors = get_neighbors(grid, index)
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if cell_state > 0: # If the cell represents an organism.
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energy = cell_state
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new_state = RULES[cell_state % len(RULES)](neighbors, energy)
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if energy >= ENERGY_THRESHOLD and grid.count(0) > 1:
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empty_spots = [i for i in range(GRID_SIZE) if grid[i] == 0]
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new_organism_position = random.choice(empty_spots)
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grid[new_organism_position] = energy // 2 # New organism created through reproduction.
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grid[index] = new_state
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elif cell_state < 0: # If the cell represents a resource.
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grid[index] = 0
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def run_simulation(grid, num_iterations):
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for _ in range(num_iterations):
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new_grid = grid.copy()
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for i in range(GRID_SIZE):
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apply_rule(new_grid, i)
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grid = new_grid
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return grid
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def display_grid(grid):
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for cell in grid:
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if cell == 0:
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print('.', end=' ')
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elif cell > 0:
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print('O', end=' ')
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else:
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print(abs(cell), end=' ')
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print()
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def main():
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grid = initialize_grid()
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display_grid(grid)
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num_iterations = 10
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grid = run_simulation(grid, num_iterations)
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print("\nSimulation Results:")
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display_grid(grid)
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if __name__ == "__main__":
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main()
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random

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