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Mohammad Azar

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers

1 author row

AAAI Conference 2018 Conference Paper

Rainbow: Combining Improvements in Deep Reinforcement Learning

Matteo Hessel
Joseph Modayil
Hado van Hasselt
Tom Schaul
Georg Ostrovski
Will Dabney
Dan Horgan
Bilal Piot

The deep reinforcement learning community has made several independent improvements to the DQN algorithm. However, it is unclear which of these extensions are complementary and can be fruitfully combined. This paper examines six extensions to the DQN algorithm and empirically studies their combination. Our experiments show that the combination provides state-of-the-art performance on the Atari 2600 benchmark, both in terms of data efﬁciency and ﬁnal performance. We also provide results from a detailed ablation study that shows the contribution of each component to overall performance.

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NeurIPS Conference 2011 Conference Paper

Speedy Q-Learning

Mohammad Ghavamzadeh
Hilbert Kappen
Mohammad Azar
Rémi Munos

We introduce a new convergent variant of Q-learning, called speedy Q-learning, to address the problem of slow convergence in the standard form of the Q-learning algorithm. We prove a PAC bound on the performance of SQL, which shows that for an MDP with n state-action pairs and the discount factor \gamma only T=O\big(\log(n)/(\epsilon^{2}(1-\gamma)^{4})\big) steps are required for the SQL algorithm to converge to an \epsilon-optimal action-value function with high probability. This bound has a better dependency on 1/\epsilon and 1/(1-\gamma), and thus, is tighter than the best available result for Q-learning. Our bound is also superior to the existing results for both model-free and model-based instances of batch Q-value iteration that are considered to be more efficient than the incremental methods like Q-learning.

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