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Mohammadreza Nakhaeinezhadfard

2 accepted papers

2025

Discrete Codebook World Models for Continuous Control

ICLR 2025poster

In reinforcement learning (RL), world models serve as internal simulators, enabling agents to predict environment dynamics and future outcomes in order to make informed decisions. While previous approaches leveraging discrete latent spaces, such as DreamerV3, have demonstrated strong performance in…

2025

Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning

AAAI 2025technical

Offline meta-reinforcement learning aims to equip agents with the ability to rapidly adapt to new tasks by training on data from a set of different tasks. Context-based approaches utilize a history of state-action-reward transitions – referred to as the context – to infer a representation of the cur…