This repository serves as a curated collection of resources, including surveys and research papers, focused on the domain of Lifelong Learning for Large Language Model (LLM) based Agents. It aims to provide a roadmap and structured overview for researchers and practitioners developing LLM agents capable of continuous learning and adaptation. The primary benefit is a centralized, organized knowledge base for this rapidly evolving field.

How It Works

The project structures the complex field of lifelong learning LLM agents around three core modules: Perception, Memory, and Action. Perception covers how agents process multimodal inputs, Memory addresses various forms of information retention (working, episodic, semantic, parametric), and Action details how agents interact with environments, utilize tools, and perform reasoning. This modular framework helps in understanding and advancing agent capabilities for incremental learning.

Quick Start & Requirements

The repository highlights the release of "LifelongAgentBench," a benchmark for lifelong learning LLM agents, with associated paper, source code, and datasets available. It also points to a comprehensive survey paper titled "Lifelong Learning of Large Language Model based Agents: A Roadmap." No direct installation or setup instructions for the repository itself are provided, as it functions as a curated list of academic resources.

Highlighted Details

• Introduction of LifelongAgentBench, a new benchmark for evaluating lifelong learning LLM agents, complete with paper, code, and datasets.
• Publication of a detailed survey paper, "Lifelong Learning of Large Language Model based Agents: A Roadmap," offering a comprehensive overview of the field.
• Systematic categorization of relevant research papers across Perception, Memory (sub-types), and Action (sub-types) modules, facilitating targeted study.

Maintenance & Community

No specific details regarding maintainers, community channels (e.g., Discord, Slack), or project roadmaps are present in the provided README content.

Licensing & Compatibility

The README content does not specify a software license for the repository or its contents, nor does it provide compatibility notes for commercial use.

Limitations & Caveats

This repository is a curated collection of academic papers and resources, not a software project with an executable component. Therefore, it does not have installation requirements, bugs, or performance limitations in the traditional software sense. Its utility is dependent on the comprehensiveness and accuracy of the collected literature.