In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
The notion of fixed-parameter approximation is introduced to investigate the approximability of optimization problems within the framework of fixed-parameter computation. This work...
Genetic algorithms are a robust adaptive optimization technique based on a biological paradigm. They perform efficient search on poorly-defined spaces by maintaining an ordered po...
This paper presents a method to capture human motion from silhouettes of a person in multi-view video streams. Applying a hierarchical kinematic body model motion parameters are e...
Christian Theobalt, Joel Carranza, Marcus A. Magno...
Inducing disjunctive and iterative macro-operators from empirical problem-solving traces provides a more powerful knowledge compilation method than simple linear macro-operators. ...