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Found 7 papers, 2 papers with code
Learning Macromanagement in StarCraft from Replays using Deep Learning
The real-time strategy game StarCraft has proven to be a challenging environment for artificial intelligence techniques, and as a result, current state-of-the-art solutions consist of numerous hand-crafted modules.
Deep Learning for Video Game Playing
In this article, we review recent Deep Learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games.
Automated Curriculum Learning by Rewarding Temporally Rare Events
We demonstrate that this \emph{Rarity of Events} (RoE) approach enables the agent to succeed in challenging VizDoom scenarios without access to the extrinsic reward from the environment.
Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation
However, when neural networks are trained in a fixed environment, such as a single level in a video game, they will usually overfit and fail to generalize to new levels.
Learning a Behavioral Repertoire from Demonstrations
Imitation Learning (IL) is a machine learning approach to learn a policy from a dataset of demonstrations.
Bootstrapping Conditional GANs for Video Game Level Generation
Theresults demonstrate that the new approach does not only gen-erate a larger number of levels that are playable but also gen-erates fewer duplicate levels compared to a standard GAN.
Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning
Recent procedural content generation via machine learning (PCGML) methods allow learning from existing content to produce similar content automatically.
