7 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.AI2009
Eligibility Propagation to Speed up Time Hopping for Reinforcement Learning
Petar Kormushev, Kohei Nomoto, Fangyan Dong +1
A mechanism called Eligibility Propagation is proposed to speed up the Time Hopping technique used for faster Reinforcement Learning in simulations. Eligibility Propagation provide…
cs.AI2009★ 3 cited
Time Hopping technique for faster reinforcement learning in simulations
Petar Kormushev, Kohei Nomoto, Fangyan Dong +1
This preprint has been withdrawn by the author for revision
cs.AI2009★ 7 cited
Time manipulation technique for speeding up reinforcement learning in simulations
Petar Kormushev, Kohei Nomoto, Fangyan Dong +1
A technique for speeding up reinforcement learning algorithms by using time manipulation is proposed. It is applicable to failure-avoidance control problems running in a computer s…