| CPC H04L 9/32 (2013.01) [G06F 9/505 (2013.01); G06F 9/54 (2013.01); G06F 16/335 (2019.01); G06F 16/345 (2019.01); G06F 21/602 (2013.01); G06F 21/6227 (2013.01); G06F 21/64 (2013.01); G06F 40/205 (2020.01); G06F 40/295 (2020.01); G06Q 10/06311 (2013.01); G06Q 10/063112 (2013.01); G06Q 10/06393 (2013.01); G06F 2209/503 (2013.01); G06F 2209/505 (2013.01)] | 20 Claims |

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1. A method, performed by at least one computer processor executing computer program instructions stored on at least one non-transitory computer-readable medium, for ranking a plurality of worker agents based on a user request, the method comprising:
(A) receiving, by a user agent, a user request including a description of a task;
(B) generating, by the user agent using a first pre-trained large language model, an embedding of the user request;
(C) identifying, by the user agent in communication with a second pretrained large language model, a plurality of tasks to be performed to process the user request;
(D) for each of a plurality of worker agents, computing a corresponding value for each of a plurality of metrics, thereby computing a plurality of metric values for each of the plurality of worker agents, wherein each of the plurality of worker agents comprises at least one model that has been trained using machine learning; and
(E) generating, for each of the plurality of worker agents, a corresponding ranking, based on the metrics computed for the plurality of worker agents in (D), thereby generating a plurality of worker agent rankings, each of which corresponds to a distinct worker agent in the plurality of worker agents.
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