Many solutions to address the challenge of robot learning have been devised, namely
through exploring novel ways for humans to communicate complex goals and tasks in …

An overarching goal of Artificial Intelligence (AI) is creating autonomous, social agents that
help people. Two important challenges, though, are that different people prefer different …

In this work, we propose a multi-objective decision making framework that accommodates
different user preferences over objectives, where preferences are learned via policy …

We consider the problem of reward maximization in the dueling bandit setup along with
constraints on resource consumption. As in the classic dueling bandits, at each round the …

Preferential Bayesian optimization (PBO) is a framework for optimizing a decision-maker's
latent preferences over available design choices. While preferences often involve multiple …

The rise of Agent AI and Large Language Model-powered Multi-Agent Systems (LLM-MAS)
has underscored the need for responsible and dependable system operation. Tools like …

Machine learning has witnessed remarkable breakthroughs in recent years. As machine
learning permeates various aspects of daily life, individuals and organizations increasingly …