1 citations · 2 across the 3 of their papers we have counts for
3 papers
Curriculum RL meets Monte Carlo Planning: Optimization of a Real World Container Management Problem
Abhijeet Pendyala, Tobias Glasmachers
In this work, we augment reinforcement learning with an inference-time collision model to ensure safe and efficient container management in a waste-sorting facility with limited pr…
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering
Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers
We present a proximal policy optimization (PPO) agent trained through curriculum learning (CL) principles and meticulous reward engineering to optimize a real-world high-throughput…
ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation
Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers +1
We present ContainerGym, a benchmark for reinforcement learning inspired by a real-world industrial resource allocation task. The proposed benchmark encodes a range of challenges c…