The Evolution of AI Agents: From Rule‐Based Systems to Autonomous Intelligence – A Comprehensive Review
Engineering Leader, Software Architect, AI & Automation Expert, Cisco ltd.
World Journal of Advanced Research and Reviews, 2024, 24(01), 2878-2887
Publication history:
Received on 02 September 2024; revised on 24 October 2024; accepted on 28 October 2024
Abstract:
Artificial Intelligence (AI) agents have evolved from early rule‐based systems to today’s sophisticated autonomous systems. This comprehensive review examines the historical development, technical advancements, and emerging trends in AI agent research. Specifically, we address the following research questions:
• How have AI agent architectures evolved over time, and what factors drove these changes?
• What are the strengths and limitations of rule‐based versus learning‐based approaches in real-world applications?
• How can ethical frameworks and empirical case studies inform future developments in AI agent technology?
This article outlines the selection criteria for the literature review, presents empirical examples from diverse application domains, and critically analyzes methodologies. It discusses both achievements and persistent challenges in AI agent research while offering recommendations for future research directions and governance.
Keywords:
Artificial Intelligence; Autonomous Intelligence; Machine Learning
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0