Search Results for author: Oswin So

Found 7 papers, 1 papers with code

Active Disruption Avoidance and Trajectory Design for Tokamak Ramp-downs with Neural Differential Equations and Reinforcement Learning

no code implementations14 Feb 2024 Allen M. Wang, Oswin So, Charles Dawson, Darren T. Garnier, Cristina Rea, Chuchu Fan

The policy training environment is a hybrid physics and machine learning model trained on simulations of the SPARC primary reference discharge (PRD) ramp-down, an upcoming burning plasma scenario which we use as a testbed.

Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian

no code implementations30 Sep 2022 Oswin So, Gongjie Li, Evangelos A. Theodorou, Molei Tao

Incorporating the Hamiltonian structure of physical dynamics into deep learning models provides a powerful way to improve the interpretability and prediction accuracy.

Astronomy

Deep Generalized Schrödinger Bridge

1 code implementation20 Sep 2022 Guan-Horng Liu, Tianrong Chen, Oswin So, Evangelos A. Theodorou

In this work, we aim at solving a challenging class of MFGs in which the differentiability of these interacting preferences may not be available to the solver, and the population is urged to converge exactly to some desired distribution.

Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM

no code implementations22 Feb 2022 Marcus A. Pereira, Augustinos D. Saravanos, Oswin So, Evangelos A. Theodorou

In this work, we propose a novel safe and scalable decentralized solution for multi-agent control in the presence of stochastic disturbances.

Collision Avoidance

Variational Inference MPC using Tsallis Divergence

no code implementations1 Apr 2021 Ziyi Wang, Oswin So, Jason Gibson, Bogdan Vlahov, Manan S. Gandhi, Guan-Horng Liu, Evangelos A. Theodorou

In this paper, we provide a generalized framework for Variational Inference-Stochastic Optimal Control by using thenon-extensive Tsallis divergence.

Model Predictive Control Variational Inference

Adaptive Risk Sensitive Model Predictive Control with Stochastic Search

no code implementations2 Sep 2020 Ziyi Wang, Oswin So, Keuntaek Lee, Camilo A. Duarte, Evangelos A. Theodorou

We present a general framework for optimizing the Conditional Value-at-Risk for dynamical systems using stochastic search.

Distributional Reinforcement Learning Optimization and Control Robotics

Cannot find the paper you are looking for? You can Submit a new open access paper.