2 papers
cs.MA2026
Expected Return Symmetries
Darius Muglich, Johannes Forkel, Elise van der Pol +1
Symmetry is an important inductive bias that can improve model robustness and generalization across many deep learning domains. In multi-agent settings, a priori known symmetries h…
cs.LG2026
Learning Abstract World Models with a Group-Structured Latent Space
Thomas Delliaux, Nguyen-Khanh Vu, Vincent François-Lavet +2
Learning meaningful abstract models of Markov Decision Processes (MDPs) is crucial for improving generalization from limited data. In this work, we show how geometric priors can be…