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Starcraft II

Starcraft II is a RTS game; the task is to train an agent to play the game.

( Image credit: The StarCraft Multi-Agent Challenge )

Papers

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Showing 126–150 of 175 papers

TitleStatusHype
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?—0
S2RMs: Spatially Structured Recurrent Modules—0
SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II—0
Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction—0
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning—0
SIDE: State Inference for Partially Observable Cooperative Multi-Agent Reinforcement Learning—0
SMAUG: A Sliding Multidimensional Task Window-Based MARL Framework for Adaptive Real-Time Subtask Recognition—0
Regularized Softmax Deep Multi-Agent Q-Learning—0
Spatially Structured Recurrent Modules—0
Spatially Structured Recurrent Modules—0
StarCraft II Build Order Optimization using Deep Reinforcement Learning and Monte-Carlo Tree Search—0
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments—0
Superhuman Game AI Disclosure: Expertise and Context Moderate Effects on Trust and Fairness—0
SVDE: Scalable Value-Decomposition Exploration for Cooperative Multi-Agent Reinforcement Learning—0
Towards a Deep Reinforcement Learning Approach for Tower Line Wars—0
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization—0
Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning—0
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning—0
Unsupervised Hebbian Learning on Point Sets in StarCraft II—0
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy GradientsCode0
CODEX: A Cluster-Based Method for Explainable Reinforcement LearningCode0
Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed AgentsCode0
Carefully Structured Compression: Efficiently Managing StarCraft II DataCode0
StarCraft II: A New Challenge for Reinforcement LearningCode0
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
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