Modeling the perceived behaviors of other agents improves the performance of an agent in multiagent interactions. We utilize the language of interactive influence diagrams to mode...
Active learning strategies can be useful when manual labeling
effort is scarce, as they select the most informative
examples to be annotated first. However, for visual category
...
Sudheendra Vijayanarasimhan (University of Texas a...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Main memory is responsible for a large and increasing fraction of the energy consumed by servers. Prior work has focused on exploiting DRAM low-power states to conserve energy. Ho...
Qingyuan Deng, David Meisner, Luiz E. Ramos, Thoma...
We present a video demonstration of an agent-based test bed application for ongoing research into multi-user, multimodal, computer-assisted meetings. The system tracks a two perso...
Edward C. Kaiser, David Demirdjian, Alexander Grue...