# Make decision decision = aagmaal.make_decision() print(decision) This code snippet demonstrates a basic implementation of the AAGMAAL framework, including the AAG governance and MAAL learning components. Note that this is a highly simplified example, and actual implementations would require more complex logic and algorithms.
import numpy as np
def acquire_knowledge(self, data): self.knowledge_base.update(data) aagmaal code
class MAALearning: def adapt(self, decision, knowledge_base): # Meta-learning logic return decision + np.random.rand() # Make decision decision = aagmaal