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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 151–175 of 175 papers

TitleStatusHype
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments—0
Superhuman Game AI Disclosure: Expertise and Context Moderate Effects on Trust and Fairness—0
SVDE: Scalable Value-Decomposition Exploration for Cooperative Multi-Agent Reinforcement Learning—0
Collaborative AI Teaming in Unknown Environments via Active Goal Deduction—0
Unsupervised Hebbian Learning on Point Sets in StarCraft II—0
Aligning Individual and Collective Objectives in Multi-Agent Cooperation—0
COA-GPT: Generative Pre-trained Transformers for Accelerated Course of Action Development in Military Operations—0
Boosting Value Decomposition via Unit-Wise Attentive State Representation for Cooperative Multi-Agent Reinforcement Learning—0
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis—0
Incorporating Pragmatic Reasoning Communication into Emergent Language—0
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors—0
Language-Guided Multi-Agent Learning in Simulations: A Unified Framework and Evaluation—0
Hierarchical Reinforcement Learning in StarCraft II with Human Expertise in Subgoals Selection—0
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning—0
Learning a Behavioral Repertoire from Demonstrations—0
BET: Explaining Deep Reinforcement Learning through The Error-Prone Decisions—0
Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning—0
Heterogeneous Learning from Demonstration—0
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II—0
Learning to Transfer Role Assignment Across Team Sizes—0
Leveraging Transformers for StarCraft Macromanagement Prediction—0
Leveraging World Model Disentanglement in Value-Based Multi-Agent Reinforcement Learning—0
HAVEN: Hierarchical Cooperative Multi-Agent Reinforcement Learning with Dual Coordination Mechanism—0
FSV: Learning to Factorize Soft Value Function for Cooperative Multi-Agent Reinforcement Learning—0
Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning—0
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