Author

Taha Shieenavaz

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Preprint Aug 2026

A Progressive Design Study of Visual Encoders and Value Estimation for Replay-Free Parallelized Q-Learning

Results show that visual topology, multiplicative representation, and downstream value-estimation design can substantially affect replay-free Q-learning, and that their benefits should be evaluated jointly with computational complexity.

Taha Shieenavaz, Shabnam Zareshahraki, L. Nanni · 0 citations

#machine learning Preprint Aug 2026

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks

Recent advancements in deep reinforcement learning have increasingly favored simplified, highly parallelized paradigms. Notably, the Parallelized Q-Network (PQN) algorithm enables off-policy value learning without relying on experience replay buffers or target networks. However, the representational capacity and comput...

Taha Shieenavaz, Shabnam Zareshahraki, L. Nanni · 0 citations