3 papers
cs.AI2026
Bayesian Expected Uncertainty Reduction (B-EUR) Model: A Computational Account of What Makes Design Options Worth Trying
Shimon Honda, Takuma Miyaguchi, Koji Koizumi +3
This paper proposes the Bayesian Expected Uncertainty Reduction (B-EUR) model, which formalizes the value of trying a candidate design action as its expected reduction of epistemic…
cs.RO2026
A Bayesian framework for the uncanny valley in humanoid robot design
Shimon Honda, Rin Shibano, Hideyoshi Yanagisawa
The uncanny valley is a long-standing empirical rule in humanoid robot design: making robots more human-like can reduce, rather than increase, affinity. Yet existing guidelines, su…
q-bio.NC2025
Evaluation of "As-Intended" Vehicle Dynamics using the Active Inference Framework
Kazuharu Kidera, Takuma Miyaguchi, Hideyoshi Yanagisawa
We constructed a computational model of the driver's brain for steering tasks using the active inference framework, grounded in the free energy principle - a theory from computatio…