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AI Summary: Defines the boundary between single-agent tools and complex 'Agentic AI' ecosystems, providing a taxonomy of challenges and solutions for multi-agent coordination.

Paper2025-05-15•Source ↗•31 attns457 checkouts

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AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges

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Ranjan Sapkota·

Konstantinos I. Roumeliotis·

Manoj Karkee

ABSTRACT

This review critically distinguishes between traditional 'AI Agents' and the broader paradigm of 'Agentic AI', offering a structured conceptual taxonomy and application mapping. The authors argue that Agentic AI represents a paradigm shift marked by multi-agent collaboration, dynamic task decomposition, persistent memory, and coordinated autonomy. The paper explores unique challenges such as hallucination compounding and coordination failure, proposing targeted solutions like advanced ReAct loops and automation coordination layers to build robust systems.

#agentic-ai/month/202505 #agentic-ai/paper/year/2025 #multi-agent-systems #taxonomy #agentic-ai/paper #agentic-ai/year/2025 #agentic-ai #cs-ai #agentic-ai/paper/month/202505 📋 al:agentic-ai-2025

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