It is well known that our prior knowledge and experiences affect how we learn new concepts. Although several formal modeling attempts have been made to quantitatively describe the ...
We describe a reinforcement learning system that transfers skills from a previously learned source task to a related target task. The system uses inductive logic programming to ana...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how local learning rules at single synapses su...
Robert A. Legenstein, Dejan Pecevski, Wolfgang Maa...
The focus of this paper is on student learning theory. Use is made of an "analytic discovery tool" called Quantitative CyberQuest (QCQ) to help conceptualize the many go...
In some environments, a learning agent must learn to balance competing objectives. For example, a Q-learner agent may need to learn which choices expose the agent to risk and whic...