This knowledge base would work as follows: when the AI suggests a solution to a specific problem based on the specified conditions, the user can confirm whether it worked or not; after that, the solution is sent to other users with the same or similar conditions. If everyone confirms that the solution works, it is added to the knowledge base, which other agents can also access. If the solution works in half of the cases, the agent can independently improve it and test it on other users until a high success rate is achieved. In this way, we obtain a database of filtered, working solutions that are almost guaranteed to work in other similar cases due to the pattern of conditions.
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