This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
This article advocates a new model for inductive learning. Called sequential induction, it helps bridge classical fixed-sample learning techniques (which are efficient but difficu...
A new inductive learning system, Lab Learning for ABduction, is presented which acquires abductive rules from a set of training examples. The goal is to nd a small knowledge base ...
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...
Guidebots, or animated pedagogical agents, can enhance interactive learning environments by promoting deeper learning and improve the learner's subjective experience. Guidebo...