Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
A common statistical problem is that of nding the median element in a set of data. This paper presents a fastand portable parallel algorithm for nding the median given a set of el...
Given a set Q of keywords, conventional keyword search (KS) returns a set of tuples, each of which (i) is obtained from a single relation, or by joining multiple relations, and (i...
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...