: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs ...
Three-dimensional structure information can be estimated from two-dimensional images using recursive estimation methods. This paper investigates possibilities to improve structure...
Fredrik Nyberg, Ola Dahl, Jan Holst, Anders Heyden
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Discrete Event Simulation (DES) has been used as a design and validation tool in various production and business applications. DES can also be utilized for analyzing the product-m...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...