【重磅综述】用于机器人操作的深度强化学习- 知乎
Promisingly, he showed that Q-learning would always “converge,” namely, as long as the system had the opportunity to try every action, from every state, as many times as necessary, it would always, eventually develop the perfect value function:
Brian Christian • The Alignment Problem
Every model, whether LLM or ML, will operate best if it is focused and specializes in specific conclusions it is trying to make. For example, I will make ChatGPT bots for very specific parts of my research, reading, and trading processes. Create specialized bots and models, then structure them hierarchically. The goal is to run a suite of bots, mod
... See moreCapital Flows • AI & the New Age of Learning
Ng and Russell’s paper had suggested that shaping rewards could enable an agent with a limited ability to look ahead and forecast the effects of its actions to behave as if it was more farsighted than it really was.