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https://github.com/Kunlun-Zhu/Awesome-Agents-Research


https://github.com/Kunlun-Zhu/Awesome-Agents-Research

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README 

        


 🤖 Awesome-Agents-Research 🎉 



## Content



- [Introduction](#introduction)

- [Repositories](#repositories)

- [Papers](#papers)

  - [Survey Paper](#agent-survery)

  - [Agent Planning](#agent-planning)

  - [Agent Memory](#agent-memory)

  - [Multi-agent Prompting & Mimicking](#multi-agent-prompting--mimicking)

- [Evaluation Benchmarks](#Evaluation-Benchmarks)

- [Welcome Contributions](#Welcome-Contributions)



## Introduction



LLM augmented autonomous agents have the potential to transform various applications by enhancing accuracy, efficiency, and automation in problem-solving. This repository contains a curated list of resources related to agent, agent planning, memory, multi-agent prompting, mimicking, and evaluation benchmarks.



## Agent Survery

- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://arxiv.org/pdf/2309.07864.pdf)

- [A Survey on Large Language Model based Autonomous Agents](https://arxiv.org/pdf/2308.11432.pdf)

- [Lilian Wang's Blog](https://lilianweng.github.io/posts/2023-06-23-agent/)



## CodeBase

- [Stable-alignment ***](http://github.com/agi-templar/Stable-Alignment)

- [AgentVerse **](https://github.com/OpenBMB/AgentVerse)

- [Camel **](https://github.com/lightaime/camel)

- [MetaGPT **](https://github.com/geekan/metagpt)

- [LangChain](https://github.com/langchain-ai/langchain)

- [AgentChain](https://github.com/jina-ai/agentchain)

  - AgentChain uses Large Language Models (LLMs) for planning and orchestrating multiple Agents or Large Models (LMs) for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data as input and output.

- [AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT)

- [GPTeam](https://github.com/101dotxyz/GPTeam)

- [SocraticAI](https://github.com/RunzheYang/SocraticAI)

- [Langroid](https://github.com/langroid/langroid)

- [Generative agents](https://github.com/Kunlun-Zhu/generative_agents)

- [Light](https://github.com/facebookresearch/LIGHT/tree/main)

- [AutoAgents](https://github.com/LinkSoul-AI/AutoAgents)

- [SuperAGI](https://github.com/TransformerOptimus/SuperAGI)

- [AI-waves:Agents](https://github.com/aiwaves-cn/agents)



## Agent Planning

- [Reasoning with Language Model is Planning with World Model](https://arxiv.org/abs/2305.14992)

- [ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models](https://arxiv.org/pdf/2305.18323.pdf)

- [Large Language Model as Autonomous Decision Maker](https://arxiv.org/abs/2308.12519)

- [LLM+P: Empowering Large Language Models with Optimal Planning Proficiency](https://arxiv.org/pdf/2304.11477.pdf)

- [Reflexion: Language Agents with Verbal Reinforcement Learning](https://arxiv.org/pdf/2303.11366.pdf)

- [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://arxiv.org/pdf/2305.10601.pdf)

- [Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models](https://arxiv.org/pdf/2305.04091v3.pdf)

- [Graph of Thoughts: Solving Elaborate Problems with Large Language Models](https://arxiv.org/pdf/2308.09687.pdf)



## Agent Memory and Single Agent

- [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://arxiv.org/pdf/2302.11382.pdf)

- [TPTU: Task Planning and Tool Usage of Large Language Model-based AI Agents](https://arxiv.org/abs/2308.03427)

- [LARGE LANGUAGE MODEL AS AUTONOMOUS DECISION MAKER](https://arxiv.org/pdf/2308.12519.pdf)

- [Cognitive Architectures for Language Agents](https://arxiv.org/pdf/2309.02427.pdf)

- [ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models](https://arxiv.org/abs/2309.00986)

- [SUSPICION-AGENT : PLAYING IMPERFECT INFORMATION GAMES WITH THEORY OF MIND AWARE GPT4](https://arxiv.org/pdf/2309.17277.pdf)

- [Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency](https://arxiv.org/pdf/2309.17382.pdf)

- [TORA: A TOOL-INTEGRATED REASONING AGENT FOR MATHEMATICAL PROBLEM SOLVING](https://arxiv.org/pdf/2309.17452.pdf)



## Multi-agent prompting & mimicking

- [Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback](https://arxiv.org/pdf/2305.10142.pdf)

- [CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society](https://arxiv.org/pdf/2303.17760.pdf)

- [ExpertPrompting: Instructing Large Language Models to be Distinguished Experts](https://arxiv.org/pdf/2305.14688.pdf)

- [Examining the Inter-Consistency of Large Language Models: An In-depth Analysis via Debate](https://arxiv.org/pdf/2305.11595.pdf)

- [Communicative Agents for Software Development](https://arxiv.org/pdf/2307.07924.pdf)

- [Unleashing Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration](https://arxiv.org/abs/2307.05300)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://arxiv.org/pdf/2304.03442v1.pdf)

- [Co-Writing Screenplays and Theatre Scripts with Language Models An Evaluation by Industry Professionals](https://arxiv.org/pdf/2209.14958.pdf)

- [Training Socially Aligned Language Models in Simulated Human Society](https://arxiv.org/pdf/2305.16960.pdf)

- [MULTI-AGENT COLLABORATION: HARNESSING THE POWER OF INTELLIGENT LLM AGENTS](https://arxiv.org/pdf/2306.03314.pdf)

- [Blind Judgement: Agent-Based Supreme Court Modelling With GPT](https://arxiv.org/pdf/2301.05327.pdf)

- [METAGPT: META PROGRAMMING FOR MULTI-AGENT COLLABORATIVE FRAMEWORK](https://arxiv.org/pdf/2308.00352v2.pdf)

- [Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate](https://arxiv.org/pdf/2305.19118.pdf)

- [Building Cooperative Embodied Agents Modularly with Large Language Models](https://arxiv.org/pdf/2307.02485.pdf)

- [Multi-Party Chat: Conversational Agents in Group Settings with Humans and Models](https://arxiv.org/pdf/2304.13835.pdf)

- [LLM as DB](https://arxiv.org/pdf/2308.05481v2.pdf)

- [BOLAA: BENCHMARKING AND ORCHESTRATING LLM-AUGMENTED AUTONOMOUS AGENTS](https://arxiv.org/pdf/2308.05960.pdf)

- [AgentSims: An Open-Source Sandbox for Large Language Model Evaluation](https://arxiv.org/pdf/2308.04026.pdf)

- [AutoGen](https://arxiv.org/pdf/2308.08155.pdf)

- [AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents](https://arxiv.org/pdf/2308.10848v1.pdf)

- [S3: Social-network Simulation System with Large Language Model-Empowered Agents](https://arxiv.org/pdf/2307.14984.pdf)

- [CGMI: Configurable General Multi-Agent Interaction Framework](https://arxiv.org/pdf/2308.12503.pdf)

- [MINDAGENT: EMERGENT GAMING INTERACTION](https://arxiv.org/pdf/2309.09971.pdf)

- [BALANCING AUTONOMY AND ALIGNMENT: A MULTI-DIMENSIONAL TAXONOMY FOR AUTONOMOUS LLM-POWERED MULTI-AGENT ARCHITECTURES](https://browse.arxiv.org/pdf/2310.03659.pdf)

- [DYNAMIC LLM-AGENT NETWORK: AN LLM-AGENT COLLABORATION FRAMEWORK WITH AGENT TEAM OPTIMIZATION](https://browse.arxiv.org/pdf/2310.02170.pdf)

- [EXPLORING COLLABORATION MECHANISMS FOR LLM AGENTS: A SOCIAL PSYCHOLOGY VIEW](https://browse.arxiv.org/pdf/2310.02124.pdf)

## Evaluation-Benchmarks

- [AgentBench](https://github.com/THUDM/AgentBench)

- [ToolBench](https://github.com/openbmb/toolbench)

- [MLAgentBench](https://github.com/snap-stanford/MLAgentBench)



## Welcome-Contributions

We need your help to build a better paper list!

You can fork this repo and make a pull request if you find more exciting papers!