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What is Q*? How Q-Learning and A* Search Combine in AI Quest Towards AGI?

What is Q*? How Q-Learning and A* Search Combine in AI Quest Towards AGI?

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Estimated reading time: 2 minutes

The ongoing developments at OpenAI have sparked considerable interest, especially regarding the alleged internal discussions among senior researchers and the board. These discussions hint at the possible creation of a precursor to Artificial General Intelligence (AGI), referred to as Q*. While the full story is yet to unfold, with figures like Elon Musk potentially sharing more information, it’s worth exploring what Q* entails and its significance.

Q* combines Q-Learning and A* Search algorithms. Q-Learning is a type of model-free reinforcement learning that helps an agent learn the value of actions in certain states to maximize rewards. It’s akin to learning how to cook a complex dish without a recipe, where each ingredient and step is a decision. Through trial and error, a “Q-table” is formed, much like recipe notes, guiding the learning process toward the optimal set of actions.

On the other hand, A* Search is an algorithm used for pathfinding and graph traversal. It’s similar to planning a complex meal, where each step in the meal preparation process is evaluated for efficiency. A* Search helps in selecting the most efficient steps to ensure all dishes are prepared in the shortest combined time.

When these two algorithms are merged into Q*, it creates a powerful system for complex problem-solving. Imagine organizing a large dinner party where A* Search plans the sequence of cooking steps for the entire meal, optimizing the process, while Q-learning perfects each dish based on past experiences. This dual approach ensures that not only each individual dish is cooked to perfection but also that the entire meal comes together efficiently.

In this hybrid model, A* Search handles the macro-management of the process, planning the overall sequence and timing, while Q-learning focuses on micro-management, refining each dish’s preparation. The goal is a perfectly timed and delicious meal that impresses guests, combining both efficiency and quality.

However, despite its potential, Q* does not signify the arrival of AGI. It lacks signs of consciousness and may not be what some envision as true AGI. Nonetheless, its capabilities could surpass those of average human workers in specific tasks, marking a significant step forward in the field of artificial intelligence.

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