We address performance issues associated with simulationbased algorithms for optimizing Markov reward processes. Specifically, we are concerned with algorithms that exploit the re...
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
We propose a lightweight traffic admission control scheme based on on-line monitoring which ensures multimedia services quality both intra-domain and end-to-end. The AC strategy i...
Solange Rito Lima, Paulo Carvalho, Alexandre Santo...
— A new biped gait generation and optimization method is proposed in the frame of Estimation of Distribution Algorithms (EDAs) with Q-learning method. By formulating the biped ga...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...