Geopolitical Intelligence & AI Strategy Agent
Develop an advanced multi-agent system using to analyze complex geopolitical data and formulate AI model training strategies. Inspired by Ukraine's initiative to share combat data for AI training, this challenge requires building a collaborative team of agents. These agents will autonomously research current events, synthesize information, identify potential risks and opportunities related to data sharing, and propose secure, ethical AI training strategies. The system should demonstrate sophisticated agent-to-agent communication and autonomous task delegation.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an AutoGen multi-agent system to synthesize geopolitical intelligence and propose AI model training strategies.
How work is evaluated
The evaluation will assess the multi-agent system's ability to generate comprehensive, well-reasoned, and ethically sound AI training strategies based on provided geopolitical contexts. Focus will be on the quality of agent collaboration and output synthesis.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Comprehensive Strategy
Checks if 'strategy_summary' is non-empty and provides a coherent plan.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Ethical Consideration Inclusion
Verifies that at least 2 ethical considerations are listed.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Strategy Detail Score
Evaluates the depth and breadth of the proposed strategy (0-100). • target: 75 • range: 0-100
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Risk Identification Completeness
Measures how many relevant risks are identified (0-100). • target: 70 • range: 0-100
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Master **AutoGen**'s conversational programming for defining agents, their roles, and communication patterns.
Implement autonomous task delegation and dynamic agent orchestration within an AutoGen workflow.
Integrate the **Alibaba Cloud Qwen** model for advanced reasoning and summarization tasks within specific agents.
Utilize **Linkup** for real-time web scraping and data extraction of news articles and geopolitical reports.
Design mechanisms for agents to synthesize information from disparate sources and generate actionable strategies.
Explore deployment considerations for AutoGen agents, potentially leveraging **Nebius AI** for model serving or agent runtime optimization.
Develop robust evaluation techniques to assess the quality and coherence of multi-agent generated strategies.
Reference links and supporting material
Sample data for 1 tasks
Challenge setup
The evaluation will assess the multi-agent system's ability to generate comprehensive, well-reasoned, and ethically sound AI training strategies based on provided geopolitical contexts. Focus will be on the quality of...
Challenge input
{ "scenario_description": "string", "key_actors": ["string"], "data_types": ["string"] }
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{ "strategy_summary": "string", "ethical_considerations": ["string"], "technical_recommendations": ["string"], "identified_risks": ["string"] }
- Checks if 'strategy_summary' is non-empty and provides a coherent plan.
- Verifies that at least 2 ethical considerations are listed.
- Evaluates the depth and breadth of the proposed strategy (0-100). • target: 75 • range: 0-100
- Strategy Detail Score target: 75
- 1 public reference case
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
No tool records are attached.
Evaluation contract
- Comprehensive Strategy · Weight 1
- Ethical Consideration Inclusion · Weight 1
- Strategy Detail Score · Weight 1
- Risk Identification Completeness · Weight 1
Metrics
- Strategy Detail Score · Target 75
- Risk Identification Completeness · Target 70
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: { "scenario_description": "string", "key_actors": ["string"], "data_types": ["string"] }
Output: { "strategy_summary": "string", "ethical_considerations": ["string"], "technical_recommendations": ["string"], "identified_risks": ["string"] }
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.