121 citations · 654 across the 70 of their papers we have counts for
10 papers · 1 filter
Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding
Yulun Zhang, Matthew C. Fontaine, Amy K. Hoover +1
We study the problem of efficiently generating high-quality and diverse content in games. Previous work on automated deckbuilding in Hearthstone shows that the quality diversity al…
Towards Transferring Human Preferences from Canonical to Actual Assembly Tasks
Heramb Nemlekar, Runyu Guan, Guanyang Luo +2
To assist human users according to their individual preference in assembly tasks, robots typically require user demonstrations in the given task. However, providing demonstrations…
Illuminating Diverse Neural Cellular Automata for Level Generation
Sam Earle, Justin Snider, Matthew C. Fontaine +2
We present a method of generating diverse collections of neural cellular automata (NCA) to design video game levels. While NCAs have so far only been trained via supervised learnin…
Robotic Lime Picking by Considering Leaves as Permeable Obstacles
Heramb Nemlekar, Ziang Liu, Suraj Kothawade +3
The problem of robotic lime picking is challenging; lime plants have dense foliage which makes it difficult for a robotic arm to grasp a lime without coming in contact with leaves.…
Design and Evaluation of a Hair Combing System Using a General-Purpose Robotic Arm
Nathaniel Dennler, Eura Shin, Maja Matarić +1
This work introduces an approach for automatic hair combing by a lightweight robot. For people living with limited mobility, dexterity, or chronic fatigue, combing hair is often a…
Personalizing User Engagement Dynamics in a Non-Verbal Communication Game for Cerebral Palsy
Nathaniel Dennler, Catherine Yunis, Jonathan Realmuto +3
Children and adults with cerebral palsy (CP) can have involuntary upper limb movements as a consequence of the symptoms that characterize their motor disability, leading to difficu…
On the Importance of Environments in Human-Robot Coordination
Matthew C. Fontaine, Ya-Chuan Hsu, Yulun Zhang +2
When studying robots collaborating with humans, much of the focus has been on robot policies that coordinate fluently with human teammates in collaborative tasks. However, less emp…
Differentiable Quality Diversity
Matthew C. Fontaine, Stefanos Nikolaidis
Quality diversity (QD) is a growing branch of stochastic optimization research that studies the problem of generating an archive of solutions that maximize a given objective functi…
Two-Stage Clustering of Human Preferences for Action Prediction in Assembly Tasks
Heramb Nemlekar, Jignesh Modi, Satyandra K. Gupta +1
To effectively assist human workers in assembly tasks a robot must proactively offer support by inferring their preferences in sequencing the task actions. Previous work has focuse…
Learning from Demonstrations using Signal Temporal Logic
Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis
Learning-from-demonstrations is an emerging paradigm to obtain effective robot control policies for complex tasks via reinforcement learning without the need to explicitly design r…