@inproceedings{sadilek2010modeling, author = {Adam Sadilek and Henry Kautz}, title = {Modeling and Reasoning about Success, Failure, and Intent of Multi-Agent Activities}, booktitle = {Mobile Context-Awareness Workshop, Twelfth {ACM} International Conference on Ubiquitous Computing}, year = {2010}, abstract = {Recent research has shown that surprisingly rich models of human activity can be learned from GPS (positional) data. However, most effort to date has concentrated on modeling single individuals or statistical properties of groups of in- dividuals. We, in contrast, take on the task of understand- ing human interactions, attempted interactions, and inten- tions from noisy sensor data in a multi-agent setting. We use a real-world game of capture the flag to illustrate our ap- proach in a well-defined domain. Our evaluation shows that given a model of successfully performed multi-agent activ- ities, along with a set of examples of failed attempts at the same activities, our system can automatically learn an aug- mented model that is capable of recognizing success, failure, as well as goals of people's actions with high accuracy. Finally, we demonstrate that explicitly modeling unsuccessful attempts boosts performance on other important recognition tasks.}, url = {http://www.cs.rochester.edu/~sadilek/Sadilek-Kautz_Modeling-Success-Failure-and-Intent_UbiComp-10.pdf} }