activity
20192026
most citedLode Encoder: AI-constrained co-creativity

15 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Learning Local Constraints for Reinforcement-Learned Content Generators

Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1

Constraint-based game content generators that learn local constraints from existing content, such as Wave Function Collapse (WFC), can generate visually satisfying game levels but…

cs.AI2025

Evolutionary Level Repair

Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1

We address the problem of game level repair, which consists of taking a designed but non-functional game level and making it functional. This might consist of ensuring the complete…

cs.LG2023★ 1 cited

Lode Enhancer: Level Co-creation Through Scaling

Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1

We explore AI-powered upscaling as a design assistance tool in the context of creating 2D game levels. Deep neural networks are used to upscale artificially downscaled patches of l…

cs.LG2023★ 15 cited

Lode Encoder: AI-constrained co-creativity

Debosmita Bhaumik, Ahmed Khalifa, Julian Togelius

We present Lode Encoder, a gamified mixed-initiative level creation system for the classic platform-puzzle game Lode Runner. The system is built around several autoencoders which a…

cs.AI2022

Predicting Personas Using Mechanic Frequencies and Game State Traces

Michael Cerny Green, Ahmed Khalifa, M Charity +2

We investigate how to efficiently predict play personas based on playtraces. Play personas can be computed by calculating the action agreement ratio between a player and a generati…

cs.AI2019★ 2 cited

Tree Search vs Optimization Approaches for Map Generation

Debosmita Bhaumik, Ahmed Khalifa, Michael Cerny Green +1

Search-based procedural content generation uses stochastic global optimization algorithms to search for game content. However, standard tree search algorithms can be competitive wi…