This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
A learner's performance does not rely only on the representation language and on the algorithm inducing a hypothesis in this language. Also the way the induced hypothesis is ...
Building robots can be a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to cope the...
We investigate an inherent limitation of top-down decision tree induction in which the continuous partitioning of the instance space progressively lessens the statistical support o...
\Ibots" (Integrating roBOTS) is a computer experiment in group learning. It is designed to understand how to use reinforcement learning to program automatically a team of robo...
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
In learning from examples it is often useful to expand an attribute-vector representation by intermediate concepts. The usual advantage of such structuring of the learning problemi...
Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Brat...