# Multi-Agent Simulations It ought to be possible, in some scenarios (particularly resource constraints and model availability) to run a continuous multi-agent simulation to iteratively improve a draft translation. One example I've implemented involves the following basic loop (each step is not necessarily blocked by the prior step): * Main translation loop * Forward translation bot drafts a new translation instance using few-shot learning based on the available example translations drafted so far by humans * Back-translation bot provides a back-translation of the new instance * Evaluation bot provides feedback on how to improve, correct, or revise the instance * repeat process until the translation draft stabilizes (if it does!) * Linguist bot builds and updates language resources, such as a multilingual project lexicon, a working grammar, machine grammar rules for output token biasing with the LLM, etc. * Project manager bot brings stable drafts to human translation team for input, feedback, and correction. Corrected drafts are added to the pool of examples available to the main translation loop. {% embed url="" %} Early POC sample using GPTeam library {% endembed %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://codex-editor.gitbook.io/project-accelerate/translators-copilot/orchestration/multi-agent-simulations.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.