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import torch
from agents.perception_module import PerceptionAgent
from agents.decision_module import DecisionAgent
from agents.action_module import ActionAgent
class MasterAgent:
def __init__(self, config):
self.perception_agent = PerceptionAgent(config)
self.decision_agent = DecisionAgent(config)
self.action_agent = ActionAgent(config)
self.reinforcement_learning = config.get("reinforcement_learning", True)
def forward(self, inputs):
# Process inputs through the perception agent
perception_output = self.perception_agent(inputs)
# Pass perception results to decision agent
decision_output = self.decision_agent(perception_output)
# Execute the chosen action
action_output = self.action_agent(decision_output)
return action_output
def learn(self, feedback):
# Implement reinforcement learning logic to adjust task allocation
if self.reinforcement_learning:
# Update sub-agent weights based on feedback
pass
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