Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
A number of Inductive Logic Programming (ILP) systems have addressed the problem of learning First Order Logic (FOL) discriminant definitions by first reformulating the FOL lear...
A pattern is a string of constant and variable symbols. The language generated by a pattern is the set of all strings of constant symbols which can be obtained from by substituti...
Thomas Erlebach, Peter Rossmanith, Hans Stadtherr,...
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...