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Starcraft

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

( Image credit: Macro Action Selection with Deep Reinforcement Learning in StarCraft )

Papers

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Showing 301–311 of 311 papers

TitleStatusHype
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?—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
Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients—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
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
State-based Episodic Memory for Multi-Agent Reinforcement Learning—0
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