Awesome Papers Autonomous Agent
Basic Information
This repository is a curated, actively maintained collection of recent research papers and resources about autonomous agents. It focuses on two main types of agents called out in the README: RL-based agents and LLM-based agents, and it organizes literature into topical sections such as instruction following, world models, language-as-knowledge, LLMs as tools, multimodal agents, multi-agent systems, benchmarks and datasets, algorithm design, continual learning and applications. The README states a scope that emphasizes recent developments rather than traditional RL agents and lists surveys, conference papers, project pages and links to code when available. The project includes a table of contents, update history and classification criteria to help readers quickly find papers relevant to planning, benchmarking, multimodality, and combinations of reinforcement learning and large language models. The collection invites issues and contributions for missing papers and is intended to track the evolving autonomous agent literature.
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