Ensemble Learning For Mega Man Level Generation
Procedural content generation via machine learning (PCGML) is the process of procedurally generating game content using models trained on existing game content. PCGML methods can struggle to capture the true variance present in underlying data with a single model. In this paper, we investigated the use of ensembles of Markov chains for procedurally generating \emph{Mega Man} levels. We conduct an initial investigation of our approach and evaluate it on measures of playability and stylistic similarity in comparison to a non-ensemble, existing Markov chain approach.
Code (0)
등록된 구현이 없습니다.
Tasks
Ensemble LearningSimilar Papers 제목 키워드 기반
Applications of Modular Co-Design for De Novo 3D Molecule Generation
De novo 3D molecule generation is a pivotal task in drug discovery. However, many recent geometric generative models struggle to produce high-quality 3D structures, even if they maintain 2D validity and topological stabi…
3D Molecule GenerationDenoisingDrug DiscoveryvalidMegaWika: Millions of reports and their sources across 50 diverse languages
To foster the development of new models for collaborative AI-assisted report generation, we introduce MegaWika, consisting of 13 million Wikipedia articles in 50 diverse languages, along with their 71 million referenced …
ArticlesCross-Lingual Question AnsweringQuestion AnsweringRetrieval+1MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation
Recently, generative adversarial networks (GANs) have shown promising performance in generating realistic images. However, they often struggle in learning complex underlying modalities in a given dataset, resulting in po…
ClusteringImage GenerationMixture-of-ExpertsMS-SSIM+1Pixel Perfect MegaMed: A Megapixel-Scale Vision-Language Foundation Model for Generating High Resolution Medical Images
Medical image synthesis presents unique challenges due to the inherent complexity and high-resolution details required in clinical contexts. Traditional generative architectures such as Generative Adversarial Networks (G…
Data AugmentationImage GenerationMedical Image GenerationAutomatic Extraction of Medication Names in Tweets as Named Entity Recognition
Social media posts contain potentially valuable information about medical conditions and health-related behavior. Biocreative VII Task 3 focuses on mining this information by recognizing mentions of medications and dieta…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)