45 citations · 145 across the 15 of their papers we have counts for
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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…