Many real-world applications of language models (LMs), such as writing assistance and
code autocomplete, involve human-LM interaction. However, most benchmarks are non …

Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …

In general-sum games the interaction of self-interested learning agents commonly leads to
collectively worst-case outcomes, such as defect-defect in the iterated prisoner's dilemma …

Communication requires having a common language, a lingua franca, between agents. This
language could emerge via a consensus process, but it may require many generations of …

We study the problem of online learning in a two-player decentralized cooperative
Stackelberg game. In each round, the leader first takes an action, followed by the follower …

Despite the advances in the autonomous driving domain, autonomous vehicles (AVs) are
still inefficient and limited in terms of cooperating with each other or coordinating with …

Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …

Assistive robot arms enable people with disabilities to conduct everyday tasks on their own.
These arms are dexterous and high-dimensional; however, the interfaces people must use …

When interacting with people, AI agents do not just influence the state of the world--they also
influence the actions people take in response to the agent, and even their underlying …

Building autonomous vehicles (AVs) is a complex problem, but enabling them to operate in
the real world where they will be surrounded by human-driven vehicles (HVs) is extremely …