Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
This paper discusses two projects aimed at utilising the educational potential of hypermedia whilst avoiding the danger of the user becoming “lost in hyperspace”. The first pr...
David J. Moore, Dave J. Hobbs, D. Mullier, C. Bell
Abstract. Robustness has long been recognised as a critical issue for coevolutionary learning. It has been achieved in a number of cases, though usually in domains which involve so...
The European Concerted Action \COMPARES" (Concerted Action on COnnectionist Methods for Preprocessing and Analysis of REmote Sensing Data) was funded within the Environment an...
Jim Austin, Giorgio Giacinto, I. Kanellopoulos, Ke...
We describe an approach to artificially evolving a drawing robot using implicit fitness functions, which are designed to minimise any direct reference to the line patterns made by ...
Jon Bird, Phil Husbands, Martin Perris, Bill Bigge...