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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 251–275 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
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets—0
Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization—0
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees—0
MMD-MIX: Value Function Factorisation with Maximum Mean Discrepancy for Cooperative Multi-Agent Reinforcement Learning—0
Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2—0
Modular Architecture for StarCraft II with Deep Reinforcement Learning—0
CGIBNet: Bandwidth-constrained Communication with Graph Information Bottleneck in Multi-Agent Reinforcement Learning—0
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games—0
Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation—0
BGC: Multi-Agent Group Belief with Graph Clustering—0
Multi-objective evolution for 3D RTS Micro—0
NeuPL: Neural Population Learning—0
Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning—0
NeuroPAL: Punctuated Anytime Learning with Neuroevolution for Macromanagement in Starcraft: Brood War—0
Never Explore Repeatedly in Multi-Agent Reinforcement Learning—0
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