Mar 18, 2021 · In this case Q-learning converges very quickly to the correct result, and double-q learning asymptotically approaches the wrong decision.

Feb 20, 2021 · 1 Answer. Q-learning is guaranteed to converge (in the tabular case) under some mild conditions, one of which is that in the limit we visit ...

Feb 21, 2021 · Given a model which is able to converge (minimize error between Q-targets and Q-values), is that model always learning to solve the levels ...

We show the new algorithm converges to the optimal policy and that it performs well in some settings in which Q-learning per- forms poorly due to its ...

Apr 26, 2021 · Q-learning will converge faster than DQN as long as you have a reasonable reward function. This is because FrozenLake has only 16 states, Q- ...

Jul 19, 2022 · It's my opinion that q-learning converges with an infinite sample. In the example, double q-learning approaches the true value faster. In a ...

Nov 9, 2021 · This paper provides sharper finite-time analysis for double Q-learning with improved convergence rate over all major parameters.

May 26, 2018 · in their paper show that Deep Double Q-Learning not only improves accuracy in estimating the action-values but also improves the policy learned.