24 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.LG2012★ 24 cited
A Dantzig Selector Approach to Temporal Difference Learning
Matthieu Geist, Bruno Scherrer, Alessandro Lazaric +1
LSTD is a popular algorithm for value function approximation. Whenever the number of features is larger than the number of samples, it must be paired with some form of regularizati…
cs.AI2012★ 1 cited
Approximate Modified Policy Iteration
Bruno Scherrer, Victor Gabillon, Mohammad Ghavamzadeh +1
Modified policy iteration (MPI) is a dynamic programming (DP) algorithm that contains the two celebrated policy and value iteration methods. Despite its generality, MPI has not bee…
cs.AI2012
On the Use of Non-Stationary Policies for Infinite-Horizon Discounted Markov Decision Processes
Bruno Scherrer
We consider infinite-horizon -discounted Markov Decision Processes, for which it is known that there exists a stationary optimal policy. We consider the algorithm Value Iteratio…