"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-08 19:02:37.456287
"""

```python
from typing import List, Dict


class ReasoningEngine:
    """
    A basic reasoning engine that can handle limited complexity tasks.
    
    This class implements a simple rule-based system to make decisions based on given conditions.
    """

    def __init__(self):
        self.rules: Dict[str, List[Dict]] = {}

    def add_rule(self, condition: str, actions: List[str]):
        """
        Adds a new rule with a specific condition and associated actions.

        :param condition: A string representing the rule's condition.
        :param actions: A list of strings indicating what actions should be taken if the condition is met.
        """
        self.rules[condition] = actions

    def evaluate(self, conditions: Dict[str, bool]) -> List[str]:
        """
        Evaluates the given conditions against all rules and returns a list of applicable actions.

        :param conditions: A dictionary where keys are rule names and values are booleans indicating whether
                           each condition is met.
        :return: A list of strings representing actions that should be taken based on matched rules.
        """
        applicable_actions = []
        for condition, actions in self.rules.items():
            if all(conditions.get(sub_condition) for sub_condition in condition.split(' ')):
                applicable_actions.extend(actions)
        return applicable_actions


# Example Usage
if __name__ == "__main__":
    reasoning_engine = ReasoningEngine()
    
    # Define rules
    reasoning_engine.add_rule("temperature_high and humidity_low", ["turn_on_fan"])
    reasoning_engine.add_rule("temperature_high or smoke_detected", ["notify_fire_department"])
    reasoning_engine.add_rule("carbon_dioxide_level_high", ["ventilate_room"])

    # Simulate conditions
    conditions = {
        "temperature_high": True,
        "humidity_low": False,
        "smoke_detected": False,
        "carbon_dioxide_level_high": True
    }

    # Evaluate rules with current conditions
    actions = reasoning_engine.evaluate(conditions)
    print("Applicable Actions:", actions)  # Expected: ['ventilate_room']
```

This example demonstrates a simple rule-based reasoning engine that can evaluate multiple conditions and execute corresponding actions based on predefined rules.