Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
Automatically constructing novel representations of tasks from analysis of state spaces is a longstanding fundamental challenge in AI. I review recent progress on this problem for...
Parameters of statistical distributions that are input to simulations are typically not known with certainty. For existing systems, or variations on existing systems, they are oft...
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Numerous simplification methods have been proposed for speeding up engineering analysis/ simulation. A recently proposed medial axis reduction is one such method, that is particul...