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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}
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