AI-Driven Smart Contracts: Enhancing Blockchain Automation with Machine Learning
Abstract
Smart contracts have revolutionized blockchain technology by enabling automated and self-executing agreements. However, traditional smart contracts are limited in their ability to handle complex, dynamic conditions that require intelligent decision-making. This paper explores the integration of AI and machine learning (ML) into smart contracts to create AI-driven smart contracts capable of adapting to changing circumstances. We propose a novel architecture where ML models are embedded within smart contracts to analyze real-time data and make informed decisions. This approach allows for more flexible and responsive contract execution, particularly in scenarios involving unpredictable variables, such as supply chain management and financial derivatives. Through case studies and simulations, we demonstrate that AI-driven smart contracts significantly enhance the functionality and efficiency of blockchain applications, paving the way for more sophisticated and autonomous blockchain ecosystems.
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References
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