"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 22:04:29.955493
"""

```python
from typing import List, Dict


class RuleBasedReasoningEngine:
    """
    A simple rule-based reasoning engine that processes a set of predefined rules to make decisions.
    """

    def __init__(self, rules: List[Dict[str, any]]):
        """
        Initialize the reasoning engine with a list of rules.

        :param rules: A list of dictionaries where each dictionary contains conditions and actions
                      for decision making.
        """
        self.rules = rules

    def apply_rules(self, data: Dict[str, any]) -> List[Dict[str, any]]:
        """
        Apply the rules to the given data and return a list of matching rule results.

        :param data: A dictionary containing input data against which rules will be applied.
        :return: A list of dictionaries where each dictionary represents a matched rule with its actions
                 and conditions.
        """
        matched_rules = []
        for rule in self.rules:
            if all(data.get(key, False) == value for key, value in rule["conditions"].items()):
                matched_rules.append(rule)
        return matched_rules

    def infer_decision(self, data: Dict[str, any]) -> str:
        """
        Infer a decision based on the applied rules.

        :param data: A dictionary containing input data against which decisions will be inferred.
        :return: The decision string resulting from applying the rules.
        """
        results = self.apply_rules(data)
        if not results:
            return "No decision can be made with the given information."
        for result in results:
            if result["action"] == "infer":
                return result.get("decision", "")
        return "Default decision applied."

# Example usage
rules = [
    {
        "conditions": {"temperature": 30, "humidity": 80},
        "action": "infer",
        "decision": "Go to the beach"
    },
    {
        "conditions": {"temperature": 15, "wind_speed": 20},
        "action": "infer",
        "decision": "Stay inside and read a book"
    }
]

engine = RuleBasedReasoningEngine(rules)
data = {"temperature": 30, "humidity": 80}
print(engine.infer_decision(data))
```