A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
The abstract mathematical theory of partial differential equations (PDEs) is formulated in terms of manifolds,scalar fields, tensors, and the like, but these algebraic structures a...
Design rules express constraints on the behavior and structure of a program. These rules can help ensure that a program follows a set of established practices, and avoids certain ...
"GP is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas...
Riccardo Poli, William B. Langdon, Nicholas Freit...