World Journal of Engineering Research and Technology

Gift Aruchi Nwatuzie*

ABSTRACT

ulti-agent systems (MAS) are pivotal in various domains requiring collaborative intelligence. However, tradi- tional data-centric approaches raise privacy, trust, and security concerns. This paper proposes an integrated framework com- bining federated learning (FL) with blockchain technology to address these challenges. Our architecture utilizes permissioned blockchain for decentralized trust management and smart con- tracts for enforcing dynamic reputationsand secure participation. We detail the methodology, implementation, and experimental evaluation in autonomous vehicles and smart grid environments. Results demonstrate significant improvements in robustness and trust assurance compared to state-of-the-art methods, validating the system’s effectiveness for real-world MAS applications. Index Terms—Federated Learning, Blockchain, Multi-Agent Systems, Trust Management, Secure Aggregation, Smart Con- tracts, Reputation Systems.

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