In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...