most citedFull Gradient DQN Reinforcement Learning: A Provably Convergent Scheme

8 citations · 8 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ML2022

A Concentration Bound for Distributed Stochastic Approximation

Harsh Dolhare, Vivek Borkar

We revisit the classical model of Tsitsiklis, Bertsekas and Athans for distributed stochastic approximation with consensus. The main result is an analysis of this scheme using the…

cs.LG2021

A Concentration Bound for LSPE()

Siddharth Chandak, Vivek S. Borkar, Harsh Dolhare

The popular LSPE() algorithm for policy evaluation is revisited to derive a concentration bound that gives high probability performance guarantees from some time on.

cs.LG2021★ 8 cited

Full Gradient DQN Reinforcement Learning: A Provably Convergent Scheme

K. E. Avrachenkov, V. S. Borkar, H. P. Dolhare +1

We analyze the DQN reinforcement learning algorithm as a stochastic approximation scheme using the o.d.e. (for 'ordinary differential equation') approach and point out certain theo…