"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-06 17:09:34.551795
"""

```python
def create_reasoning_engine(max_rules: int = 10, max_depth: int = 5) -> callable:
    """
    Creates a basic reasoning engine capable of solving limited reasoning problems.
    
    Args:
        max_rules (int): The maximum number of rules the engine can handle. Default is 10.
        max_depth (int): The maximum depth of rule application. Default is 5.

    Returns:
        callable: A function that takes a list of rules and an initial state to reason about.

    Example usage:
        >>> reasoning_engine = create_reasoning_engine(max_rules=3, max_depth=2)
        >>> rules = [Rule1(), Rule2()]
        >>> initial_state = ["A", "B"]
        >>> result = reasoning_engine(rules, initial_state)
    """

    class Rule:
        def __init__(self, condition: callable, action: callable):
            self.condition = condition
            self.action = action

        def apply(self, state) -> bool:
            return self.condition(state)

    def reasoning_engine(rules, initial_state):
        current_depth = 0
        applied_rules = set()

        def apply_rules(state, depth=0):
            nonlocal current_depth
            if current_depth < max_depth and len(applied_rules) < max_rules:
                for rule in rules:
                    if rule.apply(state) and id(rule) not in applied_rules:
                        rule.action(state)
                        applied_rules.add(id(rule))
                        apply_rules(state, depth + 1)

        apply_rules(initial_state)
        return initial_state

    return reasoning_engine


# Example Rules
class Rule1(Rule):
    def __init__(self):
        super().__init__(lambda state: "A" in state and "B" not in state, lambda state: state.append("C"))


class Rule2(Rule):
    def __init__(self):
        super().__init__(lambda state: "C" in state, lambda state: state.remove("B"))

# Example Usage
reasoning_engine = create_reasoning_engine(max_rules=3, max_depth=2)
rules = [Rule1(), Rule2()]
initial_state = ["A", "B"]
result = reasoning_engine(rules, initial_state)
print(result)  # Expected output might include changes based on applied rules.
```