We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
This study investigated the desirable characteristics of anthropomorphized learning-companion agents for college students. First, interviews with six undergraduates explored their ...
Visual categorization problems, such as object classification or action recognition,
are increasingly often approached using a detection strategy: a classifier function
is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...