The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
This paper describes a new model for understanding natural language commands given to autonomous systems that perform navigation and mobile manipulation in semi-structured environ...
Stefanie Tellex, Thomas Kollar, Steven Dickerson, ...
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
We present a background model that differentiates between background motion and foreground objects. Unlike most models that represent the variability of pixel intensity at a partic...