Starcraft

34 papers with code · Playing Games

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 )

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Greatest papers with code

StarCraft II: A New Challenge for Reinforcement Learning

16 Aug 2017deepmind/pysc2

Finally, we present initial baseline results for canonical deep reinforcement learning agents applied to the StarCraft II domain.

STARCRAFT STARCRAFT II

ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games

NeurIPS 2017 facebookresearch/ELF

In addition, our platform is flexible in terms of environment-agent communication topologies, choices of RL methods, changes in game parameters, and can host existing C/C++-based game environments like Arcade Learning Environment.

ATARI GAMES STARCRAFT

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games

1 Nov 2016TorchCraft/TorchCraft

We present TorchCraft, a library that enables deep learning research on Real-Time Strategy (RTS) games such as StarCraft: Brood War, by making it easier to control these games from a machine learning framework, here Torch.

STARCRAFT

A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning

NeurIPS 2019 TorchCraft/TorchCraftAI

While centralized reinforcement learning methods can optimally solve small MAC instances, they do not scale to large problems and they fail to generalize to scenarios different from those seen during training.

MULTI-AGENT REINFORCEMENT LEARNING STARCRAFT STRUCTURED PREDICTION

STARDATA: A StarCraft AI Research Dataset

7 Aug 2017TorchCraft/StarData

We provide full game state data along with the original replays that can be viewed in StarCraft.

IMITATION LEARNING STARCRAFT

A Dataset for StarCraft AI \& an Example of Armies Clustering

19 Nov 2012TorchCraft/StarData

We evaluated this clustering method by predicting the outcomes of battles based on armies compositions' mixtures components

STARCRAFT

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

19 Mar 2020oxwhirl/pymarl

At the same time, it is often possible to train the agents in a centralised fashion where global state information is available and communication constraints are lifted.

MULTI-AGENT REINFORCEMENT LEARNING STARCRAFT

The StarCraft Multi-Agent Challenge

11 Feb 2019oxwhirl/pymarl

In this paper, we propose the StarCraft Multi-Agent Challenge (SMAC) as a benchmark problem to fill this gap.

MULTI-AGENT REINFORCEMENT LEARNING STARCRAFT STARCRAFT II

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

ICML 2018 oxwhirl/pymarl

At the same time, it is often possible to train the agents in a centralised fashion in a simulated or laboratory setting, where global state information is available and communication constraints are lifted.

MULTI-AGENT REINFORCEMENT LEARNING STARCRAFT STARCRAFT II

MazeBase: A Sandbox for Learning from Games

23 Nov 2015facebook/MazeBase

This paper introduces MazeBase: an environment for simple 2D games, designed as a sandbox for machine learning approaches to reasoning and planning.

STARCRAFT