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Starcraft II

Starcraft II is a RTS game; the task is to train an agent to play the game.

( Image credit: The StarCraft Multi-Agent Challenge )

Papers

Showing 51100 of 175 papers

TitleStatusHype
N-Agent Ad Hoc TeamworkCode1
Meta Reinforcement Learning with Autonomous Inference of Subtask DependenciesCode1
Trajectory-Class-Aware Multi-Agent Reinforcement LearningCode1
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay BufferCode1
FoX: Formation-aware exploration in multi-agent reinforcement learningCode1
Graph Convolutional Value Decomposition in Multi-Agent Reinforcement LearningCode1
Group-Aware Coordination Graph for Multi-Agent Reinforcement LearningCode1
Gym-μRTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement LearningCode1
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement LearningCode1
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy GamesCode0
Action Semantics Network: Considering the Effects of Actions in Multiagent SystemsCode0
A Framework for Understanding and Visualizing Strategies of RL AgentsCode0
Arena: a toolkit for Multi-Agent Reinforcement LearningCode0
Carefully Structured Compression: Efficiently Managing StarCraft II DataCode0
Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed AgentsCode0
CODEX: A Cluster-Based Method for Explainable Reinforcement LearningCode0
Deep Coordination GraphsCode0
MCMARL: Parameterizing Value Function via Mixture of Categorical Distributions for Multi-Agent Reinforcement LearningCode0
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based ControlCode0
Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer LearningCode0
Explainable Reinforcement Learning Through a Causal LensCode0
EXPODE: EXploiting POlicy Discrepancy for Efficient Exploration in Multi-agent Reinforcement LearningCode0
FCMNet: Full Communication Memory Net for Team-Level Cooperation in Multi-Agent SystemsCode0
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement LearningCode0
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy GradientCode0
MSC: A Dataset for Macro-Management in StarCraft IICode0
Multi-Agent Common Knowledge Reinforcement LearningCode0
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement LearningCode0
On the Limitations of Elo: Real-World Games, are Transitive, not AdditiveCode0
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement LearningCode0
Relational Deep Reinforcement LearningCode0
Self-Motivated Multi-Agent ExplorationCode0
StarCraft II: A New Challenge for Reinforcement LearningCode0
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination DynamicsCode0
The Natural Language of ActionsCode0
TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full GameCode0
Cooperative Multi-Agent Reinforcement Learning with Hypergraph ConvolutionCode0
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy GradientsCode0
Variational Saccading: Efficient Inference for Large Resolution ImagesCode0
MARNET: Backdoor Attacks against Value-Decomposition Multi-Agent Reinforcement Learning0
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning0
Fidelity-Induced Interpretable Policy Extraction for Reinforcement Learning0
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play0
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets0
Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization0
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees0
Modular Architecture for StarCraft II with Deep Reinforcement Learning0
Towards a Deep Reinforcement Learning Approach for Tower Line Wars0
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization0
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