Results 61 to 70 of about 6,292,535 (287)
Central Path Proximal Policy Optimization
CoRRIn constrained Markov decision processes, enforcing constraints during training is often thought of as decreasing the final return. Recently, it was shown that constraints can be incorporated directly into the policy geometry, yielding an optimization trajectory close to the central path of a barrier method, which does not compromise final return ...
Nikola Milosevic +2 more
openaire +4 more sources
Truly Proximal Policy Optimization
CoRR, 2019 Proximal policy optimization (PPO) is one of the most successful deep reinforcement-learning methods, achieving state-of-the-art performance across a wide range of challenging tasks. However, its optimization behavior is still far from being fully understood.
Wang, Yuhui +3 more
openaire +4 more sources
ZX-Diagram T-Count Reduction Based on Proximal Policy Optimization
Intelligent ComputingIn fault-tolerant quantum computing systems, the T gates consume more fault-tolerant resources. In this paper, we propose an automated optimization method based on the Proximal Policy Optimization (PPO) algorithm. We first translate quantum circuits into
Keyu Xiong +3 more
doaj +1 more source
Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots
Advanced Robotics Research, EarlyView.This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou +4 more
wiley +1 more source
Satellite Trajectory Optimization via Proximal Policy Optimization for Space Debris Avoidance
IEEE AccessCollision avoidance systems are commonly used to avoid fragmentation events occuring in Low-Earth Orbit (LEO) and Geosynchronous Equatorial Orbit (GEO). However, these events have been growing in frequency as orbital congestion worsens with the launch of
Logan Luna +2 more
doaj +1 more source
Multi-object aerodynamic design optimization using deep reinforcement learning
AIP Advances, 2021 Aerodynamic design optimization is a key aspect in aircraft design. The further evolution of advanced aircraft derivatives requires a powerful optimization toolbox.
Xinyu Hui +5 more
doaj +1 more source
Um teorema de equivalencia entre metodos lagrangeano aumentado e algoritmos de pontos proximais [PDF]
, 1998 Dissertação (mestrado) - Universidade Federal de Santa Catarina. Centro de Ciências Físicas e Matemáticas.Apresentase uma prova geral do Teorema de Equivalencia que relaciona o Método de Ponto Proximal e o Método Lagrangeano Aumentado a qual inclui quase
Rezza Espinoza, Yna Consuelo
core
Advanced Robotics Research, EarlyView.DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano +3 more
wiley +1 more source
Proximal Policy Optimization-Based Power Grid Structure Optimization for Reliable Splitting
EnergiesWhen systems experience a severe fault, splitting, as the final line of defense to ensure the stability of the power system, holds immense significance.
Xinwei Sun +7 more
doaj +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source