The benefits of
The benefits of #AI #MultiAgent:
1. Each Agent of a multi-agent only pay #attention to its own #position and #information related to itself. There is no need to cover all historical information. However a single agent, such as #AutoGPT, needs to remember all historical information, which means that when a single agent faces complex tasks with a long history, the #memory #capacity (sequence length supported by a large model) is limited.
2. Through the #roleplaying mechanism, some #viewpoints from other perspectives can be excluded, making the performance of the large model more #stable. A single agent cannot do this because it is mixed with many tasks.
3. Better #scalability. The scalability of a single agent depends on some token-saving strategies of memory. For more complex tasks, the #context input to the large model will become longer each time, which will cause the risk of performance degradation (large When the model processes long sequences, key information may be lost, etc.). Multi-agent division of labor does not have this problem, because each agent only completes a #specific sub-task, and sub-tasks generally do not cause a long context.
4. Multiple solutions can be explored in #parallel, and then the #optimal solution can be selected. An individual agent lacks this benefit, making its implementation relatively challenging.