Frontiers-of-AI-Agents-Tutorial
ABOUT Sessions Learning Resources
Welcome to “Frontiers of Large Language Model-Based Agentic Systems – Construction, Efficacy and Safety” Tutorial @ CIKM 2024!
Agents hard at work! Image generated using Bing Image Creator.
Overview:
Large Language Models (LLMs) have recently demonstrated remarkable potential in achieving human-level intelligence, sparking a surge of interest in LLM-based autonomous agents. However, there is a noticeable absence of a thorough guide that methodically compiles the latest methods for building LLM-agents, their assessment, and the associated challenges. As a pioneering initiative, this tutorial delves into the intricacies of constructing LLM-based agents, providing a systematic exploration of key components and recent innovations. We dissect agent design using an established taxonomy, focusing on essential keywords prevalent in agent-related framework discussions. Key components include profiling, perception, memory, planning, and action. We unravel the intricacies of each element, emphasizing state-of-the-art techniques. Beyond individual agents, we explore the extension from single-agent paradigms to multi-agent frameworks. Participants will gain insights into orchestrating collaborative intelligence within complex environments. Additionally, we introduce and compare popular open-source frameworks for LLM-based agent development, enabling practitioners to choose the right tools for their projects. We discuss evaluation methodologies for assessing agent systems, addressing efficiency and safety concerns.
Tutorial Outline
- Introduction to Agentic Systems
- Agent Construction
- Multi-Agent Systems
- Agentic Workflow Evaluation
- Safety and Efficiency of Agentic Workflows
Checkout the detailed tutorial outline at ACM CIKM ‘24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management here
