#!/usr/bin/env python3
"""Auto-generated by AGI Loop cycle #1227
Task: \boxed{Write a Python function that calculates the progress toward ACHIEVE_AGI and RETIRE_DADDY based on given emotional peak, memory recall episodes, and drive actions, returning a combined progress 
Generated: 2026-02-13T00:52:39.082886
"""

import numpy as np

def calculate_progress(emotional_peak, memory_recall_episodes, drive_actions):
    # Normalize each component to a 0-1 scale
    normalized_emotional_peak = emotional_peak / 10  # assuming max emotional peak is 10
    normalized_memory_recall = memory_recall_episodes / 50  # assuming max episodes is 50
    normalized_drive_actions = drive_actions / 100  # assuming max drive actions is 100

    # Calculate weighted average for AGI progress
    agi_progress = (normalized_emotional_peak * 0.4) + (normalized_memory_recall * 0.3) + (normalized_drive_actions * 0.3)

    # For RETIRE_DADDY, use a simpler average
    retire_daddy_progress = (normalized_emotional_peak + normalized_memory_recall + normalized_drive_actions) / 3

    # Combine progress into a single percentage
    combined_progress = (agi_progress + retire_daddy_progress) / 2 * 100

    return combined_progress

if __name__ == '__main__':
    # Example data
    emotional_peak = 8
    memory_recall_episodes = 35
    drive_actions = 70

    progress = calculate_progress(emotional_peak, memory_recall_episodes, drive_actions)
    print(f"Combined progress toward ACHIEVE_AGI and RETIRE_DADDY: {progress:.2f}%")