Author

T. Evers

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#machine learning Preprint Oct 2026

Towards Optimal Policy Improvement

Practical Reinforcement Learning (RL) algorithms learn to solve Markov Decision Processes (MDPs) through iterative policy improvement in the presence of approximate evaluation. We study policy improvement from first principles, defining optimal policy improvement as producing the best policy attainable in a single upda...

Yaniv Oren, Viliam Vadocz, W. Zabka et al. · 0 citations

#artificial intelligence May 2026

EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control

EfficientTDMPC is introduced, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorithms that is the new state of the art in sample efficiency on HumanoidBench and the DeepMind Control Suite.

T. Evers, Cristian Meo, Wendelin Böhmer et al. · arXiv.org · 2 citations