We introduce a class of Multigrid based temporal difference algorithms for reinforcement learning with linear function approximation. Multigrid methods are commonly used to accelerate convergence of iterative numerical computation algorithms. The proposed Multigrid-enhanced TD(λ) algorithms allows to accelerate the convergence of the basic TD(λ) algorithm… (More)
– We introduce a new class of multigrid temporal-difference learning algorithms for speeding up the estimation of the value function related to a stationary policy, within the context of discounted cost Markov Decision Processes with linear functional approximation. The proposed scheme builds on the multi-grid framework which is used in numerical analysis… (More)
Cells cope with replication-blocking lesions via translesion DNA synthesis (TLS). TLS is carried out by low-fidelity DNA polymerases that replicate across lesions, thereby preventing genome instability at the cost of increased point mutations. Here we perform a two-stage siRNA-based functional screen for mammalian TLS genes and identify 17 validated TLS… (More)
Neural stem cells (NSCs) are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture) and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we… (More)
I am also indebt to Professor Irad Yavneh for his invaluable advice and support and for exposing me to field of Algebraic Multigrid.