10 papers
Active Inference as a Convex Markov Decision Process
Nikola Milosevic, Nicolás Hinrichs, Nico Scherf
Active Inference (AIF) frames adaptive behavior as the minimization of expected free energy (EFE), combining epistemic and pragmatic objectives within a single variational principl…
Predictive Statistics Shape Emergent World Representations of Grid Walkers
Sasha Brenner, Thomas R. Knösche, Nico Scherf
Next-token predictors often appear to develop internal representations of the latent world and its rules. The probabilistic nature of these models suggests a deep connection betwee…
Stochastic Decision Horizons for Constrained Reinforcement Learning
Nikola Milosevic, Leonard Franz, Daniel Haeufle +3
We propose stochastic decision horizons (SDH), a theoretically grounded framework for solving constrained RL problems with every-step constraint satisfaction, a desirable property…
Visual Bias in Simulated Users: The Impact of Luminance and Contrast on Reinforcement Learning-based Interaction
Hannah Selder, Charlotte Beylier, Nico Scherf +1
Reinforcement learning (RL) enables simulations of HCI tasks, yet their validity is questionable when performance is driven by visual rendering artifacts distinct from interaction…
Predicting Microbial Interactions Using Graph Neural Networks
Elham Gholamzadeh, Kajal Singla, Nico Scherf
Predicting interspecies interactions is a key challenge in microbial ecology, as these interactions are critical to determining the structure and activity of microbial communities.…
Multimodal Recurrent Ensembles for Predicting Brain Responses to Naturalistic Movies (Algonauts 2025)
Semih Eren, Deniz Kucukahmetler, Nico Scherf
Accurately predicting distributed cortical responses to naturalistic stimuli requires models that integrate visual, auditory and semantic information over time. We present a hierar…