A Blockchain‐Based Smart Contract Framework for Autonomous Sports Training Management in Multi‐Agent Environment

ABSTRACT In recent years, there has been a continuous growth in the demand for intelligent, decentralized and transparent systems in the field of sports training management. The combination of blockchain technology and multi‐agent systems has provided secure and trustworthy technical support for autonomous training management scenarios. This paper proposes a Blockchain‐based Autonomous Smart Contract Framework for Sports Training Management (BASM‐STM), aiming to solve key problems such as low operational efficiency, lack of trust mechanisms, and inflexible coordination mechanisms that are commonly found in traditional training platforms. This framework adopts a six‐layer architecture design, achieving a deep integration of modular smart contracts, multi‐agent collaborative decision‐making, and dynamic trust evaluation mechanisms. Its core innovation contributions are as follows: (1) Builds a modular smart contract system based on the Solidity language; (2) Designs a dynamic trust update mechanism driven by Bayesian networks; (3) Proposes a hybrid coordination engine of genetic algorithm and reinforcement learning. Experimental results show that compared with traditional centralized solutions and existing decentralized benchmark models, the comprehensive performance of BASM‐STM has been significantly improved: Orchestration latency reduced by , the session matching accuracy, fault tolerance under 5 node failures, and data tamper detection rate are all improved to varying degrees. The above experimental results verify the technical feasibility and system robustness of BASM‐STM in secure and trustworthy, intelligent and efficient sports training management scenarios.