singl3/awesome-papers-autonomous-agent

A collection of recent papers focusing on autonomous agent.

Awesome-Papers-Autonomous-Agent

This is a collection of recent papers focusing on autonomous agent. Here is how Wikipedia defines Agent:

In artificial intelligence, an intelligent agent is an agent acting in an intelligent manner; It perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or acquiring knowledge. An intelligent agent may be simple or complex: A thermostator other control systemis considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome.

Thus, the key of an agent is that it can achieve goals, acquire knowledge and continually improve. The traditional agents in RL research will not be considered in this collection. Though LLM-based agents have caught people's eyes in recent research, RL-based agents also take their special position. Specifically, this repo is interested in two types of agent: RL-based agent and LLM-based agent.

Note that this paper list is under active maintaince. Free free to open an issue if you found any missed papers that fit the topic.

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Update history

• 2023/11/08: Add papers accepted by NeurIPS'23. Add related links (project page or github) to these accepted papers 🎉
• 2023/10/25: Classify all papers based on their research topics. Check ToC for the standard of classification 👏
• 2023/10/18: Release first version of collection, including papers submitted to ICLR 2024 🚀

Table of Contents

• Awesome-Papers-Autonomous-Agent
  • Update history
  • RL-based agent
    • Instruction following
    • Build agent based on World model
    • Language as knowledge
    • LLM as a tool
    • Generalization across tasks
    • Continual learning
    • Combine RL and LLM
    • Transformer-based policy
    • Trajectory to language
    • Trajectory predication
    • Others
  • LLM-based agent
    • Multimodal
    • Train LLM for generalization & adaptation
    • Task-specific designing
    • Multi-agent (e.g., society, coperation)
    • Experimental analysis
    • Benchmark & Dataset
    • Applications
    • Algorithm design
    • Combined with RL
    • Others

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RL-based agent

Instruction following

• Natural Language-conditioned Reinforcement Learning with Inside-out Task Language Development and Translation
• Compositional Instruction Following with Language Models and Reinforcement Learning
• RT-1: Robotics Transformer for Real-World Control at Scale [blog]
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control [blog]
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models [blog]
• [NeurIPS'23] Guide Your Agent with Adaptive Multimodal Rewards [project]

Build agent based on World model

• Learning to Model the World with Language
• MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Language as knowledge

• Learning with Language Inference and Tips for Continual Reinforcement Learning
• Informing Reinforcement Learning Agents by Grounding Natural Language to Markov Decision Processes
• Language Reward Modulation for Pretraining Reinforcement Learning

LLM as a tool

• [NeurIPS'23] Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
• Leveraging Large Language Models for Optimised Coordination in Textual Multi-Agent Reinforcement Learning
• Text2Reward: Dense Reward Generation with Language Models for Reinforcement Learning
• Language to Rewards for Robotic Skill Synthesis
• Eureka: Human-Level Reward Design via Coding Large Language Models
• STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models

Generalization across tasks

• A Generalist Agent
• AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents

Continual learning

• ADAPTER-RL: Adaptation of Any Agent using Reinforcement Learning
• Online Continual Learning for Interactive Instruction Following Agents
• [NeurIPS'23] A Definition of Continual Reinforcement Learning

Combine RL and LLM

• [NeurIPS'23] Large Language Models Are Semi-Parametric Reinforcement Learning Agents
• RoboGPT : An intelligent agent of making embodied long-term decisions for daily instruction tasks
• Can Language Agents Approach the Performance of RL? An Empirical Study On OpenAI Gym
• RLAdapter: Bridging Large Language Models to Reinforcement Learning in Open Worlds

Transformer-based policy

• [NeurIPS'23] Cross-Episodic Curriculum for Transformer Agents. [project]

Trajectory to language

• [NeurIPS'23] State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
• [NeurIPS'23] Semantic HELM: A Human-Readable Memory for Reinforcement Learning
• Understanding Your Agent: Leveraging Large Language Models for Behavior Explanation

Trajectory predication

• Multi-agent Trajectory Prediction with Scalable Diffusion Transformer

Others

• Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain
• A Competition Winning Deep Reinforcement Learning Agent in microRTS
• Aligning Agents like Large Language Models

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LLM-based agent

Multimodal

• Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds
• Multimodal Web Navigation with Instruction-Finetuned Foundation Models
• You Only Look at Screens: Multimodal Chain-of-Action Agents
• Learning Embodied Vision-Language Programming From Instruction, Exploration, and Environmental Feedback
• An Embodied Generalist Agent in 3D World

Train LLM for generalization & adaptation

• FireAct: Toward Language Agent Finetuning
• Adapting LLM Agents Through Communication
• AgentTuning: Enabling Generalized Agent Abilities for LLMs
• Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Task-specific designing

• [NeurIPS'23] Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents
• [NeurIPS'23] SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks [Github]
• Rethinking the Buyer’s Inspection Paradox in Information Markets with Language Agents
• A Language-Agent Approach to Formal Theorem-Proving
• Agent Instructs Large Language Models to be General Zero-Shot Reasoners
• Ghost in the Minecraft: Hierarchical Agents for Minecraft via Large Language Models with Text-based Knowledge and Memory
• PaperQA: Retrieval-Augmented Generative Agent for Scientific Research
• Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale
• Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4

Multi-agent (e.g., society, coperation)

• Building Cooperative Embodied Agents Modularly with Large Language Models
• OKR-Agent: An Object and Key Results Driven Agent System with Hierarchical Self-Collaboration and Self-Evaluation
• MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
• AutoAgents: A Framework for Automatic Agent Generation
• Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework with Agent Team Optimization
• AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
• Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
• REX: Rapid Exploration and eXploitation for AI agents

Experimental analysis

• Identifying the Risks of LM Agents with an LM-Emulated Sandbox
• Evaluating Multi-Agent Coordination Abilities in Large Language Models
• Large Language Models as Gaming Agents
• Benchmarking Large Language Models as AI Research Agents
• Adaptive Environmental Modeling for Task-Oriented Language Agents
• CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization

Benchmark & Dataset

• SmartPlay : A Benchmark for LLMs as Intelligent Agents
• AgentBench: Evaluating LLMs as Agents
• Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena
• SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
• SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
• WebArena: A Realistic Web Environment for Building Autonomous Agents
• LLM-Deliberation: Evaluating LLMs with Interactive Multi-Agent Negotiation Game
• Evaluating Large Language Models at Evaluating Instruction Following
• CivRealm: A Learning and Reasoning Odyssey for Decision-Making Agents

Applications

• Lyfe Agents: generative agents for low-cost real-time social interactions
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Algorithm design

• [NeurIPS'23] AdaPlanner: Adaptive Planning from Feedback with Language Models [github]
• Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking
• Formally Specifying the High-Level Behavior of LLM-Based Agents
• Cumulative Reasoning With Large Language Models

Combined with RL

• [NeurIPS'23] Reflexion: language agents with verbal reinforcement learning [code]
• Teaching LLMs to Teach Themselves Better Instructions via Reinforcement Learning
• Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Others

• LUMOS: Towards Language Agents that are Unified, Modular, and Open Source
• Lemur: Harmonizing Natural Language and Code for Language Agents
• Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models