AI Agent Logic

The AI Agent Layer is the heart of ARP.

It handles:

• Reputation scoring (Oracle agent)

• Moderation & behavior evaluation (Mod agent)

• Engagement vectorization (Memory agent)

• Governance pattern recognition (Civic agent)

• Anomaly detection (Sentinel agent)

Technical Stack:

• LangChain for memory orchestration

• OpenAI / Claude / Local LLMs for contextual judgment

• Pinecone for trust vector search and user history

• Supabase for real-time score storage and retrieval

• Optional zkML: Verifiable AI decisions using RiscZero, Modulus, or Zama

Each validator’s behavior is stored, queried, and scored on a rolling basis, creating an intelligent and continuously adapting validator set.

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🔁 Block Proposal Flow (Validator Pipeline)

1. Validators ordered by reputation weight
2. Top validator proposes block
3. Co-signers selected via ARP score tiers
4. Proposal checked for compliance and reputation integrity
5. CometBFT finalizes block using rep-weighted voting
6. AI agents evaluate the block + validator behavior
7. Scores updated, rewards/slashing triggered

Validators with high rep and good governance alignment are prioritized for leadership, increasing throughput and trustworthiness.