15 citations · 19 across the 3 of their papers we have counts for
3 papers
Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics
Leonard Hinckeldey, Elliot Fosong, Rimvydas Rubavicius +6
As embodied autonomous systems capable of assisting humans in daily activities remain a major goal for robotics, efficient and appropriate reinforcement learning (RL) simulation te…
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms
Xiaocheng Tang, Fan Zhang, Zhiwei Qin +6
Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens of thousands of vehicles in a city to millions of ride demands throughout the day, providing great promises…
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning
Yan Jiao, Xiaocheng Tang, Zhiwei Qin +4
We present a new practical framework based on deep reinforcement learning and decision-time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on-dem…