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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 251–260 of 311 papers

TitleStatusHype
Leveraging World Model Disentanglement in Value-Based Multi-Agent Reinforcement Learning—0
Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition and Selective Transfer—0
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning—0
Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning—0
MAIDCRL: Semi-centralized Multi-Agent Influence Dense-CNN Reinforcement Learning—0
MARL-LNS: Cooperative Multi-agent Reinforcement Learning via Large Neighborhoods Search—0
MARNET: Backdoor Attacks against Value-Decomposition Multi-Agent Reinforcement Learning—0
Maximum Correntropy Value Decomposition for Multi-agent Deep Reinforcemen Learning—0
Meta-Learning for Planning: Automatic Synthesis of Sample Based Planners—0
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play—0
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