This is another one of those 'introductions' that is pretty technical for the average reader (including myself) but will reward the effort taken. Decentralized Training and Execution (DTE) is an AI approach where "there is no centralized controller, so the agent must choose actions on its own. In this case, agents only ever observe their own information (actions and observations) and don't observe other agent actions or observations.... DTE is used in scenarios where centralized information is unavailable or scalability is critical." We can see the practical applications almost instantly. For example, David Wiley points to this article in which decentralized agents are used to reduce bias; "each agent provides responses that reflect its assigned cultural persona and task requirements, which are then synthesized by the Multiplex Agent."
Today: 261 Total: 261 [Direct link] [Share]
