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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 101–150 of 175 papers

TitleStatusHype
CGIBNet: Bandwidth-constrained Communication with Graph Information Bottleneck in Multi-Agent Reinforcement Learning—0
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games—0
BGC: Multi-Agent Group Belief with Graph Clustering—0
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning—0
Never Explore Repeatedly in Multi-Agent Reinforcement Learning—0
NQMIX: Non-monotonic Value Function Factorization for Deep Multi-Agent Reinforcement Learning—0
Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning—0
Off-Beat Multi-Agent Reinforcement Learning—0
Offline Multi-Agent Reinforcement Learning with Coupled Value Factorization—0
Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games—0
Efficiently Scanning and Resampling Spatio-Temporal Tasks with Irregular Observations—0
Dungeon Crawl Stone Soup as an Evaluation Domain for Artificial Intelligence—0
DOP: Off-Policy Multi-Agent Decomposed Policy Gradients—0
On games and simulators as a platform for development of artificial intelligence for command and control—0
On Reinforcement Learning for Full-length Game of StarCraft—0
On Stateful Value Factorization in Multi-Agent Reinforcement Learning—0
Asynchronous Advantage Actor-Critic Agent for Starcraft II—0
A Narration-based Reward Shaping Approach using Grounded Natural Language Commands—0
Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation—0
An Approach to Partial Observability in Games: Learning to Both Act and Observe—0
POWQMIX: Weighted Value Factorization with Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning—0
Grounding Natural Language Commands to StarCraft II Game States for Narration-Guided Reinforcement Learning—0
Deep reinforcement learning with relational inductive biases—0
Deep Convolution for Irregularly Sampled Temporal Point Clouds—0
Reflection of Episodes: Learning to Play Game from Expert and Self Experiences—0
DCIR: Dynamic Consistency Intrinsic Reward for Multi-Agent Reinforcement Learning—0
Reinforcement Learning for the Beginning of Starcraft II Game—0
AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network—0
CURO: Curriculum Learning for Relative Overgeneralization—0
RMIX: Learning Risk-Sensitive Policies forCooperative Reinforcement Learning Agents—0
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents—0
RMIX: Risk-Sensitive Multi-Agent Reinforcement Learning—0
Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning—0
Role Diversity Matters: A Study of Cooperative Training Strategies for Multi-Agent RL—0
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?—0
S2RMs: Spatially Structured Recurrent Modules—0
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment—0
SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II—0
AlphaStar: An Evolutionary Computation Perspective—0
Containerized Distributed Value-Based Multi-Agent Reinforcement Learning—0
Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction—0
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning—0
SIDE: State Inference for Partially Observable Cooperative Multi-Agent Reinforcement Learning—0
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization—0
SMAUG: A Sliding Multidimensional Task Window-Based MARL Framework for Adaptive Real-Time Subtask Recognition—0
Regularized Softmax Deep Multi-Agent Q-Learning—0
Spatially Structured Recurrent Modules—0
Spatially Structured Recurrent Modules—0
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning—0
StarCraft II Build Order Optimization using Deep Reinforcement Learning and Monte-Carlo Tree Search—0
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