7 papers
AAMAS 2020, May 9–13, Auckland, New Zealand Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning∗ Extended Abstract Rose E. Wang∗ Sarah A. Wu∗ James A. Evans MIT MIT U. Chicago rewang@mit.edu sarahawu@mit.edu jevans@uchicago.edu Joshua B. Tenenbaum Davi...
. The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel machine learning algorithms fo...
. Research on multi-agent interaction involving both mul- tiple artificial agents and humans is still in its infancy. Most recent ap- proaches have focused on environments with collaboration-focused human behavior, or providing only a small, defined set of situations. When deploy...
. Responsibility is a key notion in multi-agent systems and in creating safe, reliable and ethical AI. In particular, the evaluation of choices based on responsibility is useful for making robustly good deci- sions in unpredictable domains. However, most previous work on respon-...
. The main approach to evaluating communication is by as- sessing how well it facilitates coordination. If two or more individuals can coordinate through communication, it is generally assumed that they un- derstand one another. We investigate this assumption in a signaling game...
the waiting agent off; if the agent isn’t turned off, it can proceed The off-switch game framework has been instrumental in under- to take the action. This elegant result suggests that uncertainty standing corrigibility — the property that AI agents should allow about human prefe...