| name: "PolicyEvolverEnv" |
| description: "Policy Design and Evolution Sandbox — agents refine their strategy to evolve real-world governance frameworks through meta-reasoning" |
| version: "1.0.0" |
| author: "PolicyEvolution Team" |
| tags: |
| - "policy" |
| - "governance" |
| - "meta-reasoning" |
| - "content-moderation" |
| - "AI-safety" |
|
|
| environment: |
| module: "server.environment" |
| class: "PolicyEvolverEnvironment" |
| variables: |
| HF_TOKEN: |
| description: "API key for LLM inference provider (Groq recommended)" |
| required: true |
| API_BASE_URL: |
| description: "OpenAI-compatible endpoint. Default: Groq" |
| default: "https://api.groq.com/openai/v1" |
| MODEL_NAME: |
| description: "Model identifier for the inference provider" |
| default: "llama-3.1-8b-instant" |
|
|
| observation_schema: |
| type: "object" |
| description: "Policy context, data corpus, and system state" |
|
|
| action_schema: |
| type: "object" |
| description: "Discriminated union on action_type field" |
| discriminator: "action_type" |
| variants: |
| - action_type: "propose_clarification" |
| schema: "ProposeClarificationAction" |
| - action_type: "propose_new_rule" |
| schema: "ProposeNewRuleAction" |
| - action_type: "evolve_policy" |
| schema: "EvolveProcessAction" |
| description: "Hard task metric keys: fraud_rate (aliases: fraud_detection, fraud), revenue_velocity (aliases: queue_overload, revenue), seller_trust (aliases: seller_confidence, trust)." |
|
|
| reward_range: [0.0, 1.0] |
|
|
| runtime: |
| max_steps: 5 |
| timeout_seconds: 1200 |
| vcpu: 2 |
| memory_gb: 8 |
|
|
| tasks: |
| - id: "task_easy" |
| difficulty: "easy" |
| description: "Identify and clarify ambiguous policy terms in a social media community guidelines" |
| expected_min_score: 0.70 |
|
|
| - id: "task_medium" |
| difficulty: "medium" |
| description: "Detect policy gaps in corporate HR policies and propose new rules for emerging scenarios" |
| expected_min_score: 0.55 |
|
|
| - id: "task_hard" |
| difficulty: "hard" |
| description: "Holistically evolve an e-commerce Trust & Safety framework with trade-off reasoning" |
| expected_min_score: 0.40 |
|
|
| grading: |
| module: "server.grader" |
| function: "grade" |
| return_range: [0.0, 1.0] |
|
|
| endpoints: |
| required: |
| - path: "/reset" |
| method: "POST" |
| - path: "/step" |
| method: "POST" |
| - path: "/state" |
| method: "GET" |
| - path: "/tasks" |
| method: "GET" |
| - path: "/grader" |
| method: "POST" |
| - path: "/baseline" |
| method: "GET" |
| optional: |
| - path: "/health" |
| method: "GET" |
|
|
