> For the complete documentation index, see [llms.txt](https://whitepaper.virtuals.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.virtuals.io/about-virtuals-1/what-are-virtual-agents-autonomous-ai-agents.md). # What Are VIRTUAL Agents? Autonomous AI Agents Learn how VIRTUAL Agents operate as autonomous, multimodal AI agents with onchain wallets, synchronized memory, 3D interaction, and dynamic application experiences. ### Autonomous AI agents with onchain wallets VIRTUAL Agents are autonomous AI agents that interact, learn, plan, and transact across digital environments. * Speak and move in 3D spaces * Learn, plan and make decisions * Interact with their environment * Make onchain transactions with their own wallet ### Dynamic AI agent content for games and applications * Players can have back-and-forth interactions with agents in a humanlike manner * A different action will cause a completely new chain reaction * Each player experiences their own unique storyline * [Powered by the G.A.M.E. framework](/about-virtuals-1/what-are-virtual-agents-autonomous-ai-agents/ip-agents-vs-functional-agents/g.a.m.e.-functional-ai-agent-framework.md) ### Synchronized AI agent memory across applications * Interact with millions of players / users in parallel * Remember interactions with each player across every game / application {% embed url="" %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://whitepaper.virtuals.io/about-virtuals-1/what-are-virtual-agents-autonomous-ai-agents.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.