In this paper we argue that the use of a language with a type system, together with higher-order facilities and functions, provides a suitable basis for knowledge representation in...
Peter A. Flach, Christophe G. Giraud-Carrier, John...
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
Abstract. We discuss the design of an agent for coaching collaborative learning in a distance learning context. The learning domain is entity-relationship modeling, a domain in whi...
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
In order to achieve genuine web intelligence, building some kind of large general machine-readable conceptual scheme (i.e. ontology) seems inescapable. Yet the past 20 years have ...
Samuel Sarjant, Catherine Legg, Michael Robinson, ...