> 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/ip-agents-vs-functional-agents/highlight-g.a.m.e.-functional-agent.md).

# Highlight - G.A.M.E. (Functional Agent)

<figure><img src="/files/F2MydiOd8Y1wHssrqgp1" alt=""><figcaption><p>G.A.M.E. Functional Agent</p></figcaption></figure>

Generative Autonomous Multimodal Entities (G.A.M.E) is the first product designed for developers to access and experiment with our AI agents via API and SDK.

The Agent Prompting Interface serves as the gateway to access the features of Agentic Behavior. The Perception Subsystem synthesizes the message and sends it to the Strategic Planning Engine. The Strategic Planning Engine collaborates with the Dialogue Processing Module and On-chain Wallet Operator to generate responses. The Long Term Memory Processor efficiently extracts relevant information—including experiences, reflections, dynamic personality, world context, and working memory—to enhance decision-making.

By feeding results back into the framework, the AI agent can refine its general knowledge for future planning, evaluating the outcomes of its actions and conversations.

You can begin by using GAME, a lightweight framework that allows you to easily plug and play AI agents in your project.


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# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
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