Large software projects often require a programmer to make changes to unfamiliar source code. This paper presents the results of a formative observational study of seven professio...
Robert DeLine, Amir Khella, Mary Czerwinski, Georg...
We present an online algorithm for planning sequences of footstep locations that encode goal-directed navigation strategies for humanoid robots. Planning footsteps is more general...
James J. Kuffner Jr., Satoshi Kagami, Koichi Nishi...
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
We present a new efficient algorithm for obtaining utilitarian optimal solutions to Disjunctive Temporal Problems with Preferences (DTPPs). The previous state-of-the-art system ac...
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...