26 citations · 69 across the 34 of their papers we have counts for
5 papers · 1 filter
Sample Efficient Training in Multi-Agent Adversarial Games with Limited Teammate Communication
Hardik Meisheri, Harshad Khadilkar
We describe our solution approach for Pommerman TeamRadio, a competition environment associated with NeurIPS 2019. The defining feature of our algorithm is achieving sample efficie…
A Generalized Reinforcement Learning Algorithm for Online 3D Bin-Packing
Richa Verma, Aniruddha Singhal, Harshad Khadilkar +5
We propose a Deep Reinforcement Learning (Deep RL) algorithm for solving the online 3D bin packing problem for an arbitrary number of bins and any bin size. The focus is on produci…
Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains
Nazneen N Sultana, Hardik Meisheri, Vinita Baniwal +3
This paper describes the application of reinforcement learning (RL) to multi-product inventory management in supply chains. The problem description and solution are both adapted fr…
Optimising Lockdown Policies for Epidemic Control using Reinforcement Learning
Harshad Khadilkar, Tanuja Ganu, Deva P Seetharam
In the context of the ongoing Covid-19 pandemic, several reports and studies have attempted to model and predict the spread of the disease. There is also intense debate about polic…
SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning
Somjit Nath, Richa Verma, Abhik Ray +1
We propose a generic reward shaping approach for improving the rate of convergence in reinforcement learning (RL), called Self Improvement Based REwards, or SIBRE. The approach is…