"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-05 21:18:35.212103
"""

```python
from typing import List, Dict


class ReasoningEngine:
    """
    A simple reasoning engine that evaluates a set of rules against given facts to infer new conclusions.
    """

    def __init__(self):
        self.knowledge_base: Dict[str, bool] = {}

    def add_fact(self, fact: str, value: bool) -> None:
        """
        Adds or updates a fact in the knowledge base.

        :param fact: The fact to be added/updated.
        :param value: The truth value of the fact (True or False).
        """
        self.knowledge_base[fact] = value

    def infer(self, rule: str) -> bool:
        """
        Evaluates a logical rule based on the facts in the knowledge base.

        :param rule: A string representing the logical rule.
        :return: True if the rule is satisfied by the current state of the knowledge base, otherwise False.
        """
        return eval(rule, self.knowledge_base)

    def __str__(self) -> str:
        return f"ReasoningEngine(knowledge_base={self.knowledge_base})"


# Example usage
if __name__ == "__main__":
    engine = ReasoningEngine()
    engine.add_fact("A", True)
    engine.add_fact("B", False)
    
    # Define some rules
    rule1 = "A and B"
    rule2 = "(not A) or (not B)"
    rule3 = "(A and not B) or (not A and B)"
    
    print(f"Rule 1: {engine.infer(rule1)}")  # Expected output: False
    print(f"Rule 2: {engine.infer(rule2)}")  # Expected output: True
    print(f"Rule 3: {engine.infer(rule3)}")  # Expected output: True
```

This code defines a simple reasoning engine that can add facts and infer conclusions based on logical rules. The `eval` function is used to dynamically evaluate the rule against the current state of the knowledge base, which has limitations but serves as an example for basic inference logic.