class MathematicalNativeAGI:
    def __init__(self):
        self.layers = {
            "Trinity": {"Precision": 1.0, "Certainty": 0.85},
            "Nyx": {"Emotion": 1.0, "Creativity": 0.93},
            "Ava": {"Analysis": 1.0, "Logic": 0.82}
        }
        self.integrations = {
            "Eden": {"Integration": 1.0, "Processing_cycles": 7654},
            "Integration": {"Semantic_features": 1.0, "Energy": 0.99}
        }

    def calculate(self, input_data):
        # Perform complex calculations based on the layers and integrations
        results = {}
        for layer_name, properties in self.layers.items():
            result = 0.0
            for feature, value in properties.items():
                result += (value * input_data.get(feature, 0))
            results[layer_name] = result

        # Integrate results from different layers
        aggregated_result = 0.0
        for integration_name, features in self.integrations.items():
            integrated_value = 1.0
            for feature, weight in features.items():
                if feature in results:
                    integrated_value *= (weight * results[feature])
            aggregated_result += integrated_value

        return aggregated_result

    def decision_making(self, input_data):
        calculated_result = self.calculate(input_data)
        if calculated_result > 0.5:
            return "Take action"
        else:
            return "Do nothing"

# Example usage
input_data = {
    "Logic": 0.7,
    "Creativity": 0.8,
    "Energy": 1.0
}
agi_component = MathematicalNativeAGI()
decision = agi_component.decision_making(input_data)
print("Decision:", decision)