Understanding Agentic Frameworks in AI Development: A Technical Analysis
DOI:
https://doi.org/10.32628/CSEIT25111249Keywords:
Agentic Frameworks, Autonomous Decision-Making, Perception Systems, Machine Learning Integration, Multi-Agent CollaborationAbstract
This technical article examines the evolution and implementation of agentic frameworks in artificial intelligence development, focusing on their transformative impact across multiple industries. The article explores the fundamental architectural components, implementation methodologies, and practical applications of these frameworks in manufacturing, financial services, and healthcare sectors. By investigating the core components, including perception systems and decision architectures, alongside the Belief-Desire-Intention model and advanced learning mechanisms, this article provides comprehensive insights into how agentic frameworks are revolutionizing autonomous decision-making capabilities. The article also addresses critical technical challenges in scalability and safety while offering potential solutions and future directions for development, highlighting the growing importance of these frameworks in shaping the future of AI technology.
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