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하위 태스크: 0
평가표: 16
보존된 평가 기록: 133

Bechmarks for Efficient Exploration of Completion of Multi-stage Tasks and Usage of Environmental Factors

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AnujMahajanOxf/MAVEN

공식 코드

MAVEN: Multi-Agent Variational Exploration

https://github.com/Lamperougeyxy/GHQ

공식 코드

GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning

https://github.com/PaLeroy/QVMix

공식 코드

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning

https://github.com/SimonLucas/ntbea

공식 코드

Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best

https://github.com/Sonkyunghwan/QTRAN

공식 코드

QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning

https://github.com/UTS-AAi/autoweka

공식 코드

AutoWeka4MCPS-AVATAR: Accelerating Automated Machine Learning Pipeline Composition and Optimisation

https://github.com/WentseChen/Soft-QMIX

공식 코드

Soft-QMIX: Integrating Maximum Entropy For Monotonic Value Function Factorization

https://github.com/ailabdsunipi/pymarlzooplus

공식 코드

An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks

https://github.com/camel-ai/vlm-play-starcraft2

공식 코드

AVA: Attentive VLM Agent for Mastering StarCraft II

https://github.com/chaovven/SMIX

공식 코드

SMIX($λ$): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning

https://github.com/cndota/aamas25-demar

공식 코드

Dual Ensembled Multiagent Q-Learning with Hypernet Regularizer

https://github.com/colazhang22/pps-qmix

공식 코드

PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning

https://github.com/devindeng94/llm-smac

공식 코드

A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models

https://github.com/devindeng94/smac-hard

공식 코드

SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC

https://github.com/dig-beihang/ami

공식 코드

Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence

https://github.com/gt-star-lab/jaxrobotarium

공식 코드

JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes

https://github.com/hhhusiyi-monash/UPDeT

공식 코드

UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers

https://github.com/hijkzzz/pymarl2

공식 코드

Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement Learning

https://github.com/hyeon1996/fox

공식 코드

FoX: Formation-aware exploration in multi-agent reinforcement learning

https://github.com/j3soon/dfac

공식 코드

DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning

https://github.com/jbr-ai-labs/mamba

공식 코드

Scalable Multi-Agent Model-Based Reinforcement Learning

https://github.com/jeffkinnison/shadho

공식 코드

HomOpt: A Homotopy-Based Hyperparameter Optimization Method

https://github.com/junaiddk/transmix

공식 코드

Transformer-based Value Function Decomposition for Cooperative Multi-agent Reinforcement Learning in StarCraft

https://github.com/kinalmehta/epymarl_spectral

공식 코드

Effects of Spectral Normalization in Multi-agent Reinforcement Learning

https://github.com/linkjoker1006/pymarl3

공식 코드

QTypeMix: Enhancing Multi-Agent Cooperative Strategies through Heterogeneous and Homogeneous Value Decomposition

https://github.com/liuqh16/mazero

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Efficient Multi-agent Reinforcement Learning by Planning

https://github.com/liushunyu/cia

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Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition

https://github.com/lucidrains/perceiver-pytorch

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Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models

https://github.com/lxxxxr/ices

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Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning

https://github.com/maxc01/addtree

공식 코드

Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation

https://github.com/mlr-org/mlrMBO

공식 코드

mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions

https://github.com/mooricAnna/HiSSD

공식 코드

Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation

https://github.com/navid-naderi/GraphMIX

공식 코드

Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

https://github.com/nice-hku/cl2marl-smac

공식 코드

Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning

https://github.com/nkai-decision-team/llm-pysc2

공식 코드

LLM-PySC2: Starcraft II learning environment for Large Language Models

https://github.com/openai/multiagent-particle-envs

공식 코드

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

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