We are designing a computational architecture for a "learning economy" based on personal software agents who represent users in a virtual society and assist them in find...
Many methods for quantitative structure-activity relationships (QSARs) deliver point estimates only, without quantifying the uncertainty inherent in the prediction. One way to qua...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
In this paper, we describe an exploratory study to develop a model of visual attention that could aid automatic interpretation of exophors in situated dialog. The model is intended...
Donna K. Byron, Thomas Mampilly, Vinay Sharma, Tia...