collaborators

6 papers

cs.HC2026

MyoInteract: A Framework for Fast Prototyping of Biomechanical HCI Tasks using Reinforcement Learning

Ankit Bhattarai, Hannah Selder, Florian Fischer +2

Reinforcement learning (RL)-based biomechanical simulations have the potential to revolutionise HCI research and interaction design, but currently lack usability and interpretabili…

math.OC2026

Stability and performance of stochastic economic MPC -- Stochastic characterization of the closed-loop asymptotics

Jonas Schießl, Hannah Selder, Ruchuan Ou +3

Model Predictive Control (MPC) is well understood in the deterministic setting, yet rigorous stability and performance guarantees for stochastic MPC remain limited to the considera…

cs.HC2026

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…

cs.LG2025

Attention Trajectories as a Diagnostic Axis for Deep Reinforcement Learning

Charlotte Beylier, Hannah Selder, Arthur Fleig +2

While deep reinforcement learning agents demonstrate high performance across domains, their internal decision processes remain difficult to interpret when evaluated only through pe…

cs.HC2025

Demystifying Reward Design in Reinforcement Learning for Upper Extremity Interaction: Practical Guidelines for Biomechanical Simulations in HCI

Hannah Selder, Florian Fischer, Per Ola Kristensson +1

Designing effective reward functions is critical for reinforcement learning-based biomechanical simulations, yet HCI researchers and practitioners often waste (computation) time wi…

cs.HC2025

What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation

Hannah Selder, Florian Fischer, Per Ola Kristensson +1

Biomechanical models allow for diverse simulations of user movements in interaction. Their performance depends critically on the careful design of reward functions, yet the interpl…