Search Results for author: Niels Justesen

Found 7 papers, 2 papers with code

Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning

no code implementations26 May 2020 Vanessa Volz, Niels Justesen, Sam Snodgrass, Sahar Asadi, Sami Purmonen, Christoffer Holmgård, Julian Togelius, Sebastian Risi

Recent procedural content generation via machine learning (PCGML) methods allow learning from existing content to produce similar content automatically.

Bootstrapping Conditional GANs for Video Game Level Generation

no code implementations3 Oct 2019 Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green, Niels Justesen, Sebastian Risi, Julian Togelius

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.

Image Generation

Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation

1 code implementation28 Jun 2018 Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, Sebastian Risi

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.

Dimensionality Reduction

Automated Curriculum Learning by Rewarding Temporally Rare Events

1 code implementation19 Mar 2018 Niels Justesen, Sebastian Risi

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.

Curriculum Learning

Deep Learning for Video Game Playing

no code implementations25 Aug 2017 Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi

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.

Real-Time Strategy Games

Learning Macromanagement in StarCraft from Replays using Deep Learning

no code implementations12 Jul 2017 Niels Justesen, Sebastian Risi

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.

Starcraft

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