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