Takamitsu Matsubara

Multimodal Policy Search using Overlapping Mixtures of Sparse Gaussian Process Prior

2019

In this paper, we present a novel policy search reinforcement learning algorithm that can deal with multimodality in control policies based on Gaussian processes. Our approach employs Overlapping Mixtures of Gaussian Processes (OMGPs) for a …

Domains as Objectives: Multi-Domain Reinforcement Learning with Convex-Coverage Set Learning for Domain Uncertainty Awareness

2023

Domain randomization (DR) is a powerful framework that has allowed the transfer of policies from randomized domain (a.k.a. simulation) to real robots with little to no retraining requirement. However, because the policy has to perform …