Multiagent Systems

Previously, we looked at ways to improve the quality of responses. One of these methods was the use of a multi-agent setup for configuring bots.

The use of "multi-agent approach" involves dividing the system's instructions into functional blocks and distributing them among separate bots. This helps avoid model defocusing and directs focus on performing specific tasks.

Defocusing occurs when instructions are overloaded with voluminous or ambiguous information, leading to forgetting critical points and disrupting the sequence of actions. The solution is to isolate functional blocks and reduce conditions in each instruction, which is achieved through the multi-agent approach.

Currently, there are two schemes for organizing multi-agent systems implemented in the system:

• Subordinate bot invocation. This is used when individual tasks need to be delegated from the main bot to a subordinate bot;

• Switching the active bot for a dialogue. This is applied when, at a certain stage, the dialogue needs to be transferred to a completely different bot. For example, this scheme allows for the implementation of a secretary’s role, who, depending on the interlocutor’s question, transfers the dialogue to the required department or branch (a separate bot is created for each department or branch in the system).