Training generally capable agents that perform well in unseen dynamic
en...
With the rapid progress in Multi-Agent Path Finding (MAPF), researchers ...
As human-robot interaction (HRI) systems advance, so does the difficulty...
Recent years have seen a rise in the popularity of quality diversity (QD...
Large-scale data is an essential component of machine learning as
demons...
Pre-training a diverse set of robot controllers in simulation has enable...
We present a method for generating arrangements of indoor furniture from...
Recent progress in reinforcement learning (RL) has started producing
gen...
Single-objective optimization algorithms search for the single
highest-q...
In the learning from demonstration (LfD) paradigm, understanding and
eva...
Consider a walking agent that must adapt to damage. To approach this tas...
The physical design of a robot suggests expectations of that robot's
fun...
We study the problem of efficiently generating high-quality and diverse
...
To assist human users according to their individual preference in assemb...
We present a method of generating a collection of neural cellular automa...
This work introduces an approach for automatic hair combing by a lightwe...
Children and adults with cerebral palsy (CP) can have involuntary upper ...
When studying robots collaborating with humans, much of the focus has be...
Quality diversity (QD) is a growing branch of stochastic optimization
re...
To effectively assist human workers in assembly tasks a robot must
proac...
Learning-from-demonstrations is an emerging paradigm to obtain effective...
The growth of scale and complexity of interactions between humans and ro...
Recent advancements in procedural content generation via machine learnin...
Recent developments in machine learning techniques have allowed automati...
When an AI system interacts with multiple users, it frequently needs to ...
Quality Diversity (QD) algorithms like Novelty Search with Local Competi...
People often watch videos on the web to learn how to cook new recipes,
a...
Much work in robotics and operations research has focused on optimal res...
Much work in robotics has focused on "human-in-the-loop" learning techni...
Trust is essential for human-robot collaboration and user adoption of
au...
We present a framework for learning human user models from joint-action
...