This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
We present a multiresolution framework, called Multi-Tetra framework, that approximates volume data with different levelsof-detail tetrahedra. The framework is generated through a...
In this paper we describe a compromise between generative planning and special-purpose software. Hierarchical functional models are used by an intelligent system to represent its ...
Abstract—In the real world, many applications are nonstationary optimization problems. This requires that optimization algorithms need to not only find the global optimal soluti...
We use a decomposition approach to generate cooperative strategies for a class of multi-vehicle control problems. By introducing a set of tasks to be completed by the team of vehi...