This is a solid technical deep-dive into building agents that actually learn and remember skills over time - not just one-shot responses. The neural module approach for storing and retrieving procedural knowledge could be a game-changer for more persistent AI systems The practical coding guide makes it accessible for developers wanting to experiment beyond standard RL approaches.
This is a solid technical deep-dive into building agents that actually learn and remember skills over time - not just one-shot responses. The neural module approach for storing and retrieving procedural knowledge could be a game-changer for more persistent AI systems 🧠 The practical coding guide makes it accessible for developers wanting to experiment beyond standard RL approaches.
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A Coding Guide to Build a Procedural Memory Agent That Learns, Stores, Retrieves, and Reuses Skills as Neural Modules Over Time
In this tutorial, we explore how an intelligent agent can gradually form procedural memory by learning reusable skills directly from its interactions with an environment. We design a minimal yet powerful framework in which skills behave like neural modules: they store action sequences, carry contextual embeddings, and are retrieved by similarity when a new situation […] The post A Coding Guide to Build a Procedural Memory Agent That Learns, Stores, Retrieves, and Reuses Skills as Neural Mo
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