Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
We present a method whereby an embodied agent using visual perception can efficiently create a model of a local indoor environment from its experience of moving within it. Our me...
Grace Tsai, Changhai Xu, Jingen Liu, Benjamin Kuip...
— Recent research has shown that robots can model their world with Multi-Level (ML) surface maps, which utilize ‘patches’ in a 2D grid space to represent various environment ...
Cesar Rivadeneyra, Isaac Miller, Jonathan R. Schoe...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
We present a novel framework for efficiently computing the indirect illumination in diffuse and moderately glossy scenes using density estimation techniques. Many existing global...
Robert Herzog, Vlastimil Havran, Shin-ichi Kinuwak...