Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
– Existing team training software often requires that trainees be organized as physical teams and the members of the same team be trained at the same time. To demonstrate that te...
Dianxiang Xu, Michael S. Miller, Richard A. Volz, ...
Advances in parallel computation are of central importance to Artificial Intelligence due to the significant amount of time and space their programs require. Functional languages ...