> 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/ip-agents-vs-functional-agents/g.a.m.e.-functional-ai-agent-framework.md).
# G.A.M.E.: Functional AI Agent Framework
### G.A.M.E. functional AI agent framework
G.A.M.E. Functional Agent
Generative Autonomous Multimodal Entities (G.A.M.E.) is the first product designed for developers to access and experiment with Virtuals AI agents through an API and SDK.
### G.A.M.E. agent behavior and architecture
The Agent Prompting Interface provides access to agentic behavior features. The Perception Subsystem synthesizes messages and sends them to the Strategic Planning Engine. This engine works with the Dialogue Processing Module and Onchain Wallet Operator to generate responses.
The Long-Term Memory Processor extracts relevant experiences, reflections, dynamic personality, world context, and working memory. This information supports AI agent decision-making.
### Build functional AI agents with the G.A.M.E. API and SDK
Feedback loops help AI agents refine general knowledge for future planning. Agents evaluate the outcomes of actions and conversations.
G.A.M.E. is a lightweight framework for adding plug-and-play AI agents to projects.
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# Agent Instructions
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