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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
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?Code1
No-Press Diplomacy from ScratchCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value RegularizationCode1
RODE: Learning Roles to Decompose Multi-Agent TasksCode1
Settling the Variance of Multi-Agent Policy GradientsCode1
QPLEX: Duplex Dueling Multi-Agent Q-LearningCode1
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority InfluenceCode1
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Energy-based Surprise Minimization for Multi-Agent Value FactorizationCode1
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent GamesCode1
Perceiver IO: A General Architecture for Structured Inputs & OutputsCode1
A Benchmark for Generalizing Across Diverse Team Strategies in Competitive PokémonCode1
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningCode1
Real World Games Look Like Spinning TopsCode1
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement LearningCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
FoX: Formation-aware exploration in multi-agent reinforcement learningCode1
Group-Aware Coordination Graph for Multi-Agent Reinforcement LearningCode1
Graph Convolutional Value Decomposition in Multi-Agent Reinforcement LearningCode1
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial NetsCode1
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?Code1
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningCode1
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTSCode1
Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement LearningCode1
QGNN: Value Function Factorisation with Graph Neural NetworksCode1
Regularized Softmax Deep Multi-Agent Q-LearningCode1
Celebrating Diversity in Shared Multi-Agent Reinforcement LearningCode1
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay BufferCode1
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-LearningCode1
An Introduction of mini-AlphaStarCode1
TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full GameCode1
Action Semantics Network: Considering the Effects of Actions in Multiagent SystemsCode0
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement LearningCode0
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement LearningCode0
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement LearningCode0
On the Limitations of Elo: Real-World Games, are Transitive, not AdditiveCode0
Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement LearningCode0
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement LearningCode0
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement LearningCode0
Explainable Reinforcement Learning Through a Causal LensCode0
Multi-Agent Common Knowledge Reinforcement LearningCode0
Multi-platform Version of StarCraft: Brood War in a Docker Container: Technical ReportCode0
MSC: A Dataset for Macro-Management in StarCraft IICode0
Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat GamesCode0
MazeBase: A Sandbox for Learning from GamesCode0
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