109 citations · 277 across the 50 of their papers we have counts for
6 papers · 1 filter
Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning
Md Saiful Islam, Srijita Das, Sai Krishna Gottipati +6
Recent advances in reinforcement learning (RL) and Human-in-the-Loop (HitL) learning have made human-AI collaboration easier for humans to team with AI agents. Leveraging human exp…
Tree-Based Reconstructive Partitioning: A Novel Low-Data Level Generation Approach
Emily Halina, Matthew Guzdial
Procedural Content Generation (PCG) is the algorithmic generation of content, often applied to games. PCG and PCG via Machine Learning (PCGML) have appeared in published games. How…
Game Level Blending using a Learned Level Representation
Venkata Sai Revanth Atmakuri, Seth Cooper, Matthew Guzdial
Game level blending via machine learning, the process of combining features of game levels to create unique and novel game levels using Procedural Content Generation via Machine Le…
Joint Level Generation and Translation Using Gameplay Videos
Negar Mirgati, Matthew Guzdial
Procedural Content Generation via Machine Learning (PCGML) faces a significant hurdle that sets it apart from other fields, such as image or text generation, which is limited annot…
Transfer Learning for Underrepresented Music Generation
Anahita Doosti, Matthew Guzdial
This paper investigates a combinational creativity approach to transfer learning to improve the performance of deep neural network-based models for music generation on out-of-distr…
Procedural Content Generation via Knowledge Transformation (PCG-KT)
Anurag Sarkar, Matthew Guzdial, Sam Snodgrass +3
We introduce the concept of Procedural Content Generation via Knowledge Transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which con…