most citedOnline Transfer Learning in Reinforcement Learning Domains

25 citations · 39 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2016

Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer

Yusen Zhan, Haitham Bou Ammar, Matthew E. taylor

Policy advice is a transfer learning method where a student agent is able to learn faster via advice from a teacher. However, both this and other reinforcement learning transfer me…

cs.AI2015★ 25 cited

Online Transfer Learning in Reinforcement Learning Domains

Yusen Zhan, Matthew E. Taylor

This paper proposes an online transfer framework to capture the interaction among agents and shows that current transfer learning in reinforcement learning is a special case of onl…

cs.LG2015★ 14 cited

Using PCA to Efficiently Represent State Spaces

William Curran, Tim Brys, Matthew Taylor +1

Reinforcement learning algorithms need to deal with the exponential growth of states and actions when exploring optimal control in high-dimensional spaces. This is known as the cur…