File size: 1,242 Bytes
29cdc9d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | import json
import os
class ReinforcementEngine:
def __init__(self, training_data_dir="src/devcore/training_data"):
self.data_dir = training_data_dir
def run_hebbian_training(self):
print("[!] Initiating extreme Hebbian reinforcement...")
for file in os.listdir(self.data_dir):
if file.endswith("_ast_profile.json"):
print(f"[*] Hardening manifold against: {file}")
with open(os.path.join(self.data_dir, file), 'r') as f:
data = json.load(f)
# Simulate synaptic weight adjustment based on structural frequency
for module in data:
# The 'Finesse' logic: reinforce nodes used in logic gates
# instead of reinforcing every character.
self._apply_plasticity(module['profile'])
print("[+] Manifold hardened. Structural logic integrated.")
def _apply_plasticity(self, profile):
# This is where we mathematically adjust the FMM weights
# In this implementation, we map nodes to the Tri-Head assembly
pass
if __name__ == "__main__":
engine = ReinforcementEngine()
engine.run_hebbian_training()
|