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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 226250 of 311 papers

TitleStatusHype
Off-Policy Multi-Agent Decomposed Policy GradientsCode1
Value-Decomposition Multi-Agent Actor-CriticsCode1
Artificial Intelligence is stupid and causal reasoning won't fix it0
QTRAN++: Improved Value Transformation for Cooperative Multi-Agent Reinforcement Learning0
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningCode1
Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition and Selective Transfer0
StarCraft II Build Order Optimization using Deep Reinforcement Learning and Monte-Carlo Tree Search0
Learning to Play No-Press Diplomacy with Best Response Policy IterationCode1
Incorporating Pragmatic Reasoning Communication into Emergent Language0
Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningCode1
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization0
The Adversarial Resilience Learning Architecture for AI-based Modelling, Exploration, and Operation of Complex Cyber-Physical Systems0
Optimal Any-Angle Pathfinding on a Sphere0
Real World Games Look Like Spinning TopsCode1
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning0
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningCode2
FACMAC: Factored Multi-Agent Centralised Policy GradientsCode1
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial NetsCode1
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI0
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets0
Heterogeneous Learning from Demonstration0
Reinforcement Learning-based Application Autoscaling in the Cloud: A Survey0
Meta Reinforcement Learning with Autonomous Inference of Subtask DependenciesCode1
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement LearningCode1
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