Multi-Agent User Behavior Simulation
This challenge involves building a sophisticated multi-agent system to model and predict user interactions on a digital platform. Participants will use OpenAI o3 for advanced reasoning capabilities and AutoGen to orchestrate a team of autonomous agents that interact via an A2A protocol. Each agent will embody a distinct user persona, capable of extended thinking and decision-making within a simulated environment. The system will leverage MCP-enabled tools to interact with the simulated platform's API, generating realistic behavioral data for product testing and market analysis.
AI Research & Mentorship
What you are building
The core problem, expected build, and operating context for this challenge.
This challenge involves building a sophisticated multi-agent system to model and predict user interactions on a digital platform. Participants will use OpenAI o3 for advanced reasoning capabilities and AutoGen to orchestrate a team of autonomous agents that interact via an A2A protocol. Each agent will embody a distinct user persona, capable of extended thinking and decision-making within a simulated environment. The system will leverage MCP-enabled tools to interact with the simulated platform's API, generating realistic behavioral data for product testing and market analysis.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master AutoGen for creating and managing a team of goal-driven, conversational agents with specific roles and objectives for user simulation
Implement A2A protocol for secure and efficient agent-to-agent communication, enabling agents to observe, react, and collaborate within a simulated environment
Design complex user personas and behavioral scripts, leveraging OpenAI o3's advanced reasoning to generate realistic and varied user actions, preferences, and decision paths
Develop MCP-enabled tool integration modules that allow AutoGen agents to interact with a simulated web application's API, performing actions like browsing, clicking, purchasing, or commenting
Build extended thinking pipelines where agents can deliberate, plan, and strategize their actions over multiple steps, simulating more complex user journeys and problem-solving scenarios
Deploy a robust logging and analytics system to capture and analyze the simulated user behavior, providing insights into user flows, pain points, and success metrics
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Operating window
Key dates and the organization behind this challenge.
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