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From the 1 of 7 linked papers with an AI index.

collaborators

7 papers

cs.AI2026

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details

Maksymilian Wolski, Nicholas Hoernle, Johannes Forkel +1

AI agents deployed in real-world settings must be capable of coordinating with humans and other AI agents they have not encountered before. Zero-shot coordination (ZSC) algorithms…

cs.LG2026

Fully Offline Reinforcement Learning

Mattie Fellows, Clarisse Wibault, Uljad Berdica +3

The paper proposes fully offline reinforcement learning methods that use Bayesian model-based techniques to learn dynamics and evaluate policies without any online interaction, ena…

cs.NE2026

Evolving Many Worlds: Towards Open-Ended Discovery in Petri Dish NCA via Population-Based Training

Uljad Berdica, Jakob Foerster, Frank Hutter +1

The generation of sustained, open-ended complexity from local interactions remains a fundamental challenge in artificial life. Differentiable multi-agent systems, such as Petri Dis…

cs.MA2026

Modelling Opinion Dynamics at Scale with Deep MARL

Lukas Seier, Brandon Kaplowitz, Sebastian Towers +2

Modelling opinion dynamics typically relies on hand-crafted local interaction rules to study emergent macroscopic phenomena such as consensus and polarisation. In contrast, multi-a…

cs.LG2026

High entropy leads to symmetry-equivariant policies in Dec-POMDPs

Johannes Forkel, Constantin Ruhdorfer, Michael Beukman +2

We prove that in any Dec-POMDP, sufficiently high entropy regularization ensures that the policy gradient flow with tabular softmax parametrization always converges, for any initia…

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…