# BossKaMagic
A comprehensive Python package containing AI algorithm implementations including genetic algorithms, propositional logic solvers, and Bayes theorem applications.
## Features
### 🧬 Genetic Algorithms
- **8-Queens Problem Solver**: Genetic algorithm implementation to solve the classic 8-Queens puzzle
- **Traveling Salesman Problem (TSP)**: Genetic algorithm for finding optimal routes
### 🧠Logic & Probability
- **Propositional Logic**: Complete logical operators (AND, OR, NOT, IMPLIES, BICONDITIONAL) with truth tables
- **Logic Solver**: Truth table generation, resolution theorem proving, and DPLL satisfiability checking
- **Bayes Theorem**: Conditional probability calculations and medical diagnosis examples
- **Naive Bayes Classifier**: Simple implementation for classification tasks
## Installation
```bash
pip install bosskamagic
```
## Quick Start
### Genetic Algorithm - 8 Queens
```python
from bosskamagic.eight_queens_genetic import SimpleQueensGA
# Solve 8-Queens problem
solver = SimpleQueensGA()
solution = solver.solve()
print(f"Solution found: {solution}")
```
### Genetic Algorithm - TSP
```python
from bosskamagic.tsp_genetic import City, SimpleTSPGA
# Create cities
cities = [
City("A", 0, 0),
City("B", 1, 2),
City("C", 3, 1),
City("D", 2, 3)
]
# Solve TSP
tsp_solver = SimpleTSPGA(cities)
best_tour, best_distance = tsp_solver.solve()
print(f"Best distance: {best_distance}")
```
### Logical Operators
```python
from bosskamagic.logic_and_bayes import LogicalOperators
# Use logical operators
result = LogicalOperators.AND(True, False)
print(f"True AND False = {result}")
# Print truth tables
LogicalOperators.print_truth_table_basic()
```
### Bayes Theorem
```python
from bosskamagic.logic_and_bayes import BayesTheorem
# Calculate conditional probability
prob = BayesTheorem.conditional_probability(0.8, 0.1, 0.05)
print(f"Posterior probability: {prob}")
# Run medical diagnosis example
BayesTheorem.medical_diagnosis_example()
```
## Modules
- `eight_queens_genetic`: Genetic algorithm for 8-Queens problem
- `tsp_genetic`: Genetic algorithm for Traveling Salesman Problem
- `logic_and_bayes`: Propositional logic and Bayes theorem implementations
## Requirements
- Python >= 3.7
- random2 >= 1.0.1
## License
MIT License
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## Author
Your Name - your.email@example.com
## Keywords
genetic-algorithm, artificial-intelligence, 8-queens, tsp, traveling-salesman, propositional-logic, bayes-theorem, machine-learning
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