We present a new approach to 3D scene modeling based on geometric constraints. Contrary to the existing methods, we can quickly obtain 3D scene models that respect the given const...
Marta Wilczkowiak, Gilles Trombettoni, Christophe ...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
As many real-world problems involve user preferences, costs, or probabilities, constraint satisfaction has been extended to optimization by generalizing hard constraints to soft co...
: A shape design sensitivity analysis and optimization procedure is proposed using a meshfree method. A CAD tool connection is established to facilitate the seamless integration of...
Iulian Grindeanu, Nam Ho Kim, Kung K. Choi, Jiun-S...
Combinatorial optimization problems expressed as Boolean constraint satisfaction problems (BCSPs) arise in several contexts, ranging from the classical unate set-packing problems ...