Victoria VR Intelligence Core
Last updated
Last updated
The Victoria VR Intelligence Core is a cutting-edge AI framework serving as the central engine for powering intelligent agents across the Victoria VR ecosystem. Designed to be modular, scalable, and adaptable, it acts as the backbone for a network of AI-driven agents, ensuring consistency, intelligence, and seamless performance throughout the platform.
This framework enables agents to perceive, reason, plan, and act efficiently, creating an interactive and dynamic environment that meets the demands of an evolving ecosystem.
Memory System
The Memory System is at the heart of the Intelligence Core, allowing agents to store, retrieve, and process data effectively.
Short-Term Memory:
Manages active and immediate data for fast decision-making.
Long-Term Memory:
Knowledge Base: A structured repository of reusable, persistent information.
Conversation Store: Tracks dialogue history to maintain conversational continuity.
Episodic Memory: Captures specific experiences to enhance learning and decision-making.
Data Store & Profiler: Aggregate, organize, and optimize data for improved agent performance.
Perception System
The Perception Layer gathers and processes different types of inputs, like text, images, and sounds, to help the VR Intelligence Core understand its surroundings as a whole.
Planning
The AI Core incorporates advanced Planning and Reasoning modules that enable agents to operate efficiently and intelligently.
Reflection: Analyze past actions and outcomes to optimize future performance.
Reasoning: Use logical analysis to navigate complex decisions and challenges.
Decomposition: Break down large, complex tasks into manageable, executable steps.
Tools (Actions)
The AI Core integrates tools that enable agents to execute actions dynamically.
Knowledge Retrieval: Access relevant information from the Knowledge Base.
Web Search: Perform real-time data acquisition from external sources.
API Calls: Connect with external services and systems for enhanced functionality.
System Components: Leverage platform-specific tools for executing specialized tasks.
Step 1: User Input The process starts when the user provides input in the form of text, images, audio, or other data types.
Step 2: Perception System The input is sent to the Perception System, which processes and interprets the data. This system acts as the “eyes and ears” of the AI, analyzing and understanding the user's request.
Step 3: Intelligence Core The interpreted data is then passed to the Intelligence Core, the central engine of the system. Here, the AI retrieves relevant information from Short-Term Memory (for immediate data) and Long-Term Memory (for knowledge and past experiences).
Step 4: Planning Using the retrieved data, the Intelligence Core formulates an action plan. This involves:
Reflection: Analyzing past outcomes to optimize the current task.
Reasoning: Applying logical decision-making to solve challenges.
Decomposition: Breaking down complex tasks into smaller, manageable steps.
Step 5: Tools (Actions) Once the plan is ready, the Intelligence Core activates Tools (Actions) to execute the task. These tools perform specific actions such as accessing databases, performing web searches, connecting APIs, or generating outputs like text, images, or audio.
Step 6: Environment Interaction The tools interact with the environment as needed, while the Perception System continuously monitors for any changes or new data.
Step 7: Output to the User Finally, the system delivers the results back to the user. These outputs can take the form of a text-based reply, images, audio, or completed tasks, depending on the original request.
Avatar Agents
Agents with distinct identities, personalities, or roles within the metaverse or social platforms.
Utility Agents
Agents built to handle foundational tasks like data analysis, execution of commands, and automation.
Synergy Agents
Agents blend immersive engagement with task efficiency, providing users with a seamless, interactive, and functional experience.
