src/core/integration_layer.py

class SymbolicProcessor:
    def process(self, input_data):
        # Implement symbolic processing logic
        return {"symbolic_result": input_data}

class NeuralProcessor:
    def process(self, input_data):
        # Implement neural processing logic
        return {"neural_result": input_data}

class IntegrationLayer:
    def __init__(self):
        self.symbolic_processor = SymbolicProcessor()
        self.neural_processor = NeuralProcessor()
        self.semiotic_processor = SemioticProcessor()

    def process_input(self, input_data):
        # Bidirectional processing between symbolic and subsymbolic systems
        neural_output = self.neural_processor.process(input_data)
        symbolic_output = self.symbolic_processor.process(input_data)
        semiotic_interpretation = self.semiotic_processor.interpret(
            neural_output,
            symbolic_output
        )
        return self._integrate_outputs(
            neural_output,
            symbolic_output,
            semiotic_interpretation
        )

    def _integrate_outputs(self, neural_output, symbolic_output, semiotic_interpretation):
        # Implement integration logic
        return {
            "neural": neural_output,
            "symbolic": symbolic_output,
            "semiotic": semiotic_interpretation
        }

class SemioticProcessor:
    def __init__(self):
        self.sign_levels = ['syntactic', 'semantic', 'pragmatic']

    def interpret(self, neural_output, symbolic_output):
        # Multi-level sign processing implementation
        return {"interpretation": self.sign_levels}