Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
Decision making models for autonomous agents have received increased attention, particularly in the field of intelligent robots. In this paper we will show how a Defeasible Logic ...
Combining various knowledge types - and reasoning methods - in knowledge-based systems is a challenge to the knowledge representation task. The paper describes an object-oriented,...
Large databases of linguistic annotations are used for testing linguistic hypotheses and for training language processing models. These linguistic annotations are often syntactic ...
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...