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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

Showing 5175 of 311 papers

TitleStatusHype
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-LearningCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team CompositionCode1
An Introduction of mini-AlphaStarCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTSCode1
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent GamesCode1
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningCode1
Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement LearningCode1
TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full GameCode1
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement LearningCode1
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?Code1
Multi-Agent Collaboration via Reward Attribution DecompositionCode1
Graph Convolutional Value Decomposition in Multi-Agent Reinforcement LearningCode1
RODE: Learning Roles to Decompose Multi-Agent TasksCode1
Energy-based Surprise Minimization for Multi-Agent Value FactorizationCode1
QPLEX: Duplex Dueling Multi-Agent Q-LearningCode1
Off-Policy Multi-Agent Decomposed Policy GradientsCode1
Value-Decomposition Multi-Agent Actor-CriticsCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningCode1
Learning to Play No-Press Diplomacy with Best Response Policy IterationCode1
Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningCode1
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