Effective collaboration between humans and agents depends on humans maintaining an
appropriate understanding of and calibrated trust in the judgment of their agent counterparts …

Reinforcement learning is the area of machine learning concerned with learning which
actions to execute in an unknown environment in order to maximize cumulative reward. As …

Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating
to solve a single task together and other times dividing it up into sub‐tasks to work on in …

Recent advances in multi-agent reinforcement learning (MARL) have achieved super-
human performance in games like Quake 3 and Dota 2. Unfortunately, these techniques …

© 2020 International Foundation for Autonomous Agents and Multiagent Systems
(IFAAMAS). All rights reserved. Humans collaborate in dynamic and flexible ways …

As autonomous AI agents proliferate in the real world, they will increasingly need to
cooperate with each other to achieve complex goals without always being able to coordinate …

Collaboration requires agents to align their goals on the fly. Underlying the human ability to
align goals with other agents is their ability to predict the intentions of others and actively …

Open ad hoc teamwork is the problem of training a single agent to efficiently collaborate with
an unknown group of teammates whose composition may change over time. A variable team …

Simulators are being increasingly used to train agents before deploying them in real-world
environments. While training in simulation provides a cost-effective way to learn, poorly …

Zero-sum games have long guided artificial intelligence research, since they possess both a
rich strategy space of best-responses and a clear evaluation metric. What's more …