We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
Abstract. In this paper, we present the results of a pilot study of a human robot interaction experiment where the rhythm of the interaction is used as a reinforcement signal to le...
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
Designing the dialogue strategy of a spoken dialogue system involves many nontrivial choices. This paper presents a reinforcement learning approach for automatically optimizing di...
Diane J. Litman, Michael S. Kearns, Satinder P. Si...