224 citations · 308 across the 17 of their papers we have counts for
4 papers · 1 filter
Pixels to Keys: Exploring Spatial and Motion Cues in Gameplay Inverse Dynamics
Abhishek Pillai, Ekta Prashnani, Joohwan Kim +1
Video games offer scalable environments for studying perception and control in embodied agents. Abundant online gameplay videos could supply demonstrations, but they rarely include…
Training a Conditioned Video Game Agent on a VLM Annotated Dataset
Katrin Schmid, Iuri Frosio
Reinforcement Learning (RL) is a powerful but far from easy-to-use technique for policy learning. In the specific case of video games, access to the game engine is required to get…
VLMs for Videogame Data Annotation
Katrin Schmid, Iuri Frosio
Vision Language Models (VLMs) and Artificial Intelligence (AI) agents have revolutionized how engineers approach complex problems in real-world applications. Their adoption in vide…
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Assaf Hallak, Gal Dalal, Steven Dalton +3
Tree Search (TS) is crucial to some of the most influential successes in reinforcement learning. Here, we tackle two major challenges with TS that limit its usability: \textit{dist…