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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

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Showing 161–170 of 311 papers

TitleStatusHype
Forecasting Evolution of Clusters in Game Agents with Hebbian Learning—0
A Framework for Understanding and Visualizing Strategies of RL AgentsCode0
Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2—0
Maximum Correntropy Value Decomposition for Multi-agent Deep Reinforcemen Learning—0
Unsupervised Hebbian Learning on Point Sets in StarCraft II—0
Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games—0
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement LearningCode0
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
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis—0
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