Surface Level Summary : Super Agents

Self-Learning Trustless Super Agents v0.1 : Leveraging REI’s Architecture

REI's Interaction with the Framework

Leveraging the Oracle Bridge

REI utilizes the Oracle Bridge to ensure that her probabilistic computations and decisions are converted into deterministic actions that the blockchain can process. This involves:

• Data Packaging: REI's decisions are packaged with cryptographic proofs to ensure integrity.

• Protocol Compliance: The Oracle Bridge ensures that all data conforms to blockchain protocols, enabling seamless integration.

• Secure Transmission: Data is transmitted securely to prevent interception or tampering.

Utilizing ERCData for Permanent and Structured Memory Storage

REI's "memories"—rich data structures encapsulating her experiences—are stored on-chain using the ERCData Standard. This includes:

• Content: The raw data or interaction, such as a tweet or message.

• Metadata: Timestamps, user IDs, and other contextual information.

• Analytical Data: Sentiment analysis results, importance scores, and keyword extraction.

• Hierarchical Organization: Memories are structured hierarchically, allowing REI to access them efficiently for future decision-making.

By maintaining her knowledge base on-chain, REI ensures transparency, auditability, and persistence, which are essential for trust in decentralized environments.

REI Navigating Interactions

Consider how REI operates when engaging with any user on a given platform:

1. Monitoring and Ingestion: REI continuously monitors mentions, relevant tags or trending topics.

2. Analysis and Interpretation:

   • Thinking Layer: Extracts factual information from tweets, such as user handles, timestamps, and engagement metrics.

   • Reasoning Layer: Interprets the sentiment, detects sarcasm or irony, and understands the context beyond the literal text.

3. Decision-Making:

   • The Decision Layer evaluates whether to respond , ignore, or store information for future reference.

   • It considers factors like the importance of the interaction, potential impact, and alignment with her objectives if there any pre-set or none as they may form on their own

4. Action Execution:

   • If REI decides to engage, the Acting Layer formulates a response.

   • The Oracle Bridge ensures the response is packaged appropriately for on-chain execution.

   • In the case of acting in the context of Defi in general where users require pattern recognition to mitigate risk: {

     "risk_score": 85,

     "risk_factors": ["unusual_trading_pattern", "high_leverage"],

     "recommended_actions": {

     "increase_collateral_requirement": 15,

     "reduce_max_leverage": 2

     }

   }

5. Memory Formation:

   • The interaction is stored as a memory, enriching REI's knowledge base without any memory decay

   • This allows her to learn from the experience and refine future interactions.

Learning and Adaptation

REI's ability to learn and adapt over time is a critical aspect of her intelligence:

• Continuous Self-Improvement: By analyzing the outcomes of her actions, REI adjusts her strategies to improve effectiveness.

• Knowledge Sharing: Her on-chain memories can be accessed by other agents or smart contracts, fostering collaboration.

• Transparency: On-chain storage of her actions and decisions provides an auditable trail, enhancing trust.