Abstract. Accurate selectivity estimations are essential for query optimization decisions where they are typically derived from various kinds of histograms which condense value dis...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
This work studies the mGA operator (Micro Genetic Algorithm), that has been proposed in literature as a “local search” operator for optimization with Genetic Algorithm. A new ...
It is well known that stochastic control systems can be viewed as Markov decision processes (MDPs) with continuous state spaces. In this paper, we propose to apply the policy iter...
Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automa...
Branislav Kveton, Milos Hauskrecht, Carlos Guestri...