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Starcraft II
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Starcraft II is a RTS game; the task is to train an agent to play the game.
<span style="color:grey; opacity: 0.6">( Image credit: The StarCraft Multi-Agent Challenge )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Never Explore Repeatedly in Multi-Agent Reinforcement Learning
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning
Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization
Offline Multi-Agent Reinforcement Learning with Coupled Value Factorization
Semantic HELM: A Human-Readable Memory for Reinforcement Learning
EXPODE: EXploiting POlicy Discrepancy for Efficient Exploration in Multi-agent Reinforcement Learning
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?
Boosting Value Decomposition via Unit-Wise Attentive State Representation for Cooperative Multi-Agent Reinforcement Learning
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning
Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information Principles
SVDE: Scalable Value-Decomposition Exploration for Cooperative Multi-Agent Reinforcement Learning
AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence
TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems
Self-Motivated Multi-Agent Exploration
CURO: Curriculum Learning for Relative Overgeneralization
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy Gradient
On Efficient Reinforcement Learning for Full-length Game of StarCraft II
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees
Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning
A Framework for Understanding and Visualizing Strategies of RL Agents
Transformer-based Value Function Decomposition for Cooperative Multi-agent Reinforcement Learning in StarCraft
Unsupervised Hebbian Learning on Point Sets in StarCraft II
SC2EGSet: StarCraft II Esport Replay and Game-state Dataset
Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning
On the Limitations of Elo: Real-World Games, are Transitive, not Additive
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis
Off-Beat Multi-Agent Reinforcement Learning
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning
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