3 papers
cs.LG2026
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
Seyed Mahdi B. Azad, Jasper Hoffmann, Iman Nematollahi +3
Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enforcing a low-rank factorization. Howeve…
cs.LG2025
Fill in the Blanks: Accelerating Q-Learning with a Handful of Demonstrations in Sparse Reward Settings
Seyed Mahdi Basiri Azad, Joschka Boedecker
Reinforcement learning (RL) in sparse-reward environments remains a significant challenge due to the lack of informative feedback. We propose a simple yet effective method that use…
cs.LG2025
SR-Reward: Taking The Path More Traveled
Seyed Mahdi B. Azad, Zahra Padar, Gabriel Kalweit +1
In this paper, we propose a novel method for learning reward functions directly from offline demonstrations. Unlike traditional inverse reinforcement learning (IRL), our approach d…