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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 51100 of 311 papers

TitleStatusHype
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-LearningCode1
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
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
Real World Games Look Like Spinning TopsCode1
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial NetsCode1
Meta Reinforcement Learning with Autonomous Inference of Subtask DependenciesCode1
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement LearningCode1
The StarCraft Multi-Agent ChallengeCode1
Towards Accurate Generative Models of Video: A New Metric & ChallengesCode1
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningCode1
Counterfactual Multi-Agent Policy GradientsCode1
Stabilising Experience Replay for Deep Multi-Agent Reinforcement LearningCode1
Transformer World Model for Sample Efficient Multi-Agent Reinforcement LearningCode0
NeuroPAL: Punctuated Anytime Learning with Neuroevolution for Macromanagement in Starcraft: Brood War0
Language-Guided Multi-Agent Learning in Simulations: A Unified Framework and Evaluation0
Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning0
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning0
Nucleolus Credit Assignment for Effective Coalitions in Multi-agent Reinforcement Learning0
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement LearningCode0
Reflection of Episodes: Learning to Play Game from Expert and Self Experiences0
Cooperative Multi-Agent Planning with Adaptive Skill Synthesis0
Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning0
Innovative activities of Activision Blizzard: A patent network analysis0
Superhuman Game AI Disclosure: Expertise and Context Moderate Effects on Trust and Fairness0
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination DynamicsCode0
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors0
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement LearningCode0
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