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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

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Showing 51–100 of 175 papers

TitleStatusHype
TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning ProblemsCode1
Self-Motivated Multi-Agent ExplorationCode0
CURO: Curriculum Learning for Relative Overgeneralization—0
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning—0
Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy GradientCode0
On Efficient Reinforcement Learning for Full-length Game of StarCraft IICode2
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees—0
Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction—0
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning—0
A Framework for Understanding and Visualizing Strategies of RL AgentsCode0
Transformer-based Value Function Decomposition for Cooperative Multi-agent Reinforcement Learning in StarCraftCode1
Unsupervised Hebbian Learning on Point Sets in StarCraft II—0
SC2EGSet: StarCraft II Esport Replay and Game-state DatasetCode1
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games—0
On the Limitations of Elo: Real-World Games, are Transitive, not AdditiveCode0
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?—0
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay BufferCode1
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis—0
Off-Beat Multi-Agent Reinforcement Learning—0
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II—0
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning—0
Learning to Transfer Role Assignment Across Team Sizes—0
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed AgentsCode0
Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation—0
MCMARL: Parameterizing Value Function via Mixture of Categorical Distributions for Multi-Agent Reinforcement LearningCode0
FCMNet: Full Communication Memory Net for Team-Level Cooperation in Multi-Agent SystemsCode0
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy GradientsCode0
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning—0
CGIBNet: Bandwidth-constrained Communication with Graph Information Bottleneck in Multi-Agent Reinforcement Learning—0
Cooperative Multi-Agent Reinforcement Learning with Hypergraph ConvolutionCode0
Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC TasksCode1
Regularized Softmax Deep Multi-Agent Q-LearningCode1
RMIX: Learning Risk-Sensitive Policies forCooperative Reinforcement Learning Agents—0
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven ExplorationCode1
Coordinated Proximal Policy OptimizationCode1
On games and simulators as a platform for development of artificial intelligence for command and control—0
Containerized Distributed Value-Based Multi-Agent Reinforcement Learning—0
HAVEN: Hierarchical Cooperative Multi-Agent Reinforcement Learning with Dual Coordination Mechanism—0
Leveraging Transformers for StarCraft Macromanagement Prediction—0
TiKick: Towards Playing Multi-agent Football Full Games from Single-agent DemonstrationsCode1
Role Diversity Matters: A Study of Cooperative Training Strategies for Multi-Agent RL—0
MARNET: Backdoor Attacks against Value-Decomposition Multi-Agent Reinforcement Learning—0
Applying supervised and reinforcement learning methods to create neural-network-based agents for playing StarCraft IICode1
An Approach to Partial Observability in Games: Learning to Both Act and Observe—0
Rethinking of AlphaStarCode1
Perceiver IO: A General Architecture for Structured Inputs & OutputsCode1
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement LearningCode1
Context-Aware Sparse Deep Coordination GraphsCode1
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