2 papers
cs.RO2025
Learning Human Reaching Optimality Principles from Minimal Observation Inverse Reinforcement Learning
Sarmad Mehrdad, Maxime Sabbah, Vincent Bonnet +1
This paper investigates the application of Minimal Observation Inverse Reinforcement Learning (MO-IRL) to model and predict human arm-reaching movements with time-varying cost weig…
cs.LG2025
Cost Function Estimation Using Inverse Reinforcement Learning with Minimal Observations
Sarmad Mehrdad, Avadesh Meduri, Ludovic Righetti
We present an iterative inverse reinforcement learning algorithm to infer optimal cost functions in continuous spaces. Based on a popular maximum entropy criteria, our approach ite…