AI Model Architecture

Multi-Layer Neural Networks

• AI agents leverage deep learning models, including multi-layer neural networks trained on diverse DeFi datasets.

• These models excel in tasks like pattern recognition, anomaly detection, and predictive analytics.

Federated Learning Framework

• Federated learning enables AI models to be trained collaboratively across multiple nodes without sharing raw data.

• This approach enhances privacy and decentralization while continuously improving model performance.

Reinforcement Learning for Strategy Optimization

• Reinforcement learning algorithms allow AI agents to adaptively optimize their strategies.

• By simulating potential outcomes, agents learn to maximize rewards while minimizing risks.

Explainable AI (XAI)

• DonutSwap prioritizes transparency with explainable AI techniques, allowing users to understand the rationale behind each agent’s decision.

• Users gain confidence in AI-driven processes with clear visualizations and detailed decision trees.