no code implementations • 1 Sep 2021 • Marcus A. Pereira, Camilo A. Duarte, Ioannis Exarchos, Evangelos A. Theodorou
In this paper, we introduce a novel deep learning based solution to the Powered-Descent Guidance (PDG) problem, grounded in principles of nonlinear Stochastic Optimal Control (SOC) and Feynman-Kac theory.
1 code implementation • 30 Mar 2021 • Keenon Werling, Dalton Omens, Jeongseok Lee, Ioannis Exarchos, C. Karen Liu
We present a fast and feature-complete differentiable physics engine, Nimble (nimblephysics. org), that supports Lagrangian dynamics and hard contact constraints for articulated rigid body simulation.
1 code implementation • 8 Mar 2021 • Ioannis Exarchos, Brian H. Do, Fabio Stroppa, Margaret M. Coad, Allison M. Okamura, C. Karen Liu
Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms, while improving safety, lowering cost, and providing an increased workspace, with potential application in home environments.
Robotics
no code implementations • 21 Nov 2020 • Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou
We showcase superior performance of our framework over the state-of-the-art deep fictitious play algorithm on an inter-bank lending/borrowing problem in terms of multiple metrics.
1 code implementation • 3 Nov 2020 • Ioannis Exarchos, Yifeng Jiang, Wenhao Yu, C. Karen Liu
Transferring reinforcement learning policies trained in physics simulation to the real hardware remains a challenge, known as the "sim-to-real" gap.
no code implementations • 28 Sep 2020 • Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos Theodorou
In this paper we present a deep learning framework for solving large-scale multi-agent non-cooperative stochastic games using fictitious play.
no code implementations • 2 Sep 2020 • Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou
This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints.
no code implementations • ICLR 2021 • Ioannis Exarchos, Marcus A. Pereira, Ziyi Wang, Evangelos A. Theodorou
In this work we propose the use of adaptive stochastic search as a building block for general, non-convex optimization operations within deep neural network architectures.
no code implementations • 11 Jun 2019 • Ziyi Wang, Keuntaek Lee, Marcus A. Pereira, Ioannis Exarchos, Evangelos A. Theodorou
This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems.