20 citations · 53 across the 14 of their papers we have counts for
14 papers
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce
Omkar Shelke, Pranavi Pathakota, Anandsingh Chauhan +3
This paper presents an integrated algorithmic framework for minimising product delivery costs in e-commerce (known as the cost-to-serve or C2S). One of the major challenges in e-co…
DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces
Pranavi Pathakota, Hardik Meisheri, Harshad Khadilkar
The ability to learn robust policies while generalizing over large discrete action spaces is an open challenge for intelligent systems, especially in noisy environments that face t…
Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning
Harshad Khadilkar, Hardik Meisheri
A significant challenge in reinforcement learning is quantifying the complex relationship between actions and long-term rewards. The effects may manifest themselves over a long seq…
A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management
Hardik Meisheri, Somjit Nath, Mayank Baranwal +1
Most existing literature on supply chain and inventory management consider stochastic demand processes with zero or constant lead times. While it is true that in certain niche scen…
Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning
Durgesh Kalwar, Omkar Shelke, Somjit Nath +2
Improving sample efficiency is a key challenge in reinforcement learning, especially in environments with large state spaces and sparse rewards. In literature, this is resolved eit…
Learning to Minimize Cost-to-Serve for Multi-Node Multi-Product Order Fulfilment in Electronic Commerce
Pranavi Pathakota, Kunwar Zaid, Anulekha Dhara +4
We describe a novel decision-making problem developed in response to the demands of retail electronic commerce (e-commerce). While working with logistics and retail industry busine…
School of hard knocks: Curriculum analysis for Pommerman with a fixed computational budget
Omkar Shelke, Hardik Meisheri, Harshad Khadilkar
Pommerman is a hybrid cooperative/adversarial multi-agent environment, with challenging characteristics in terms of partial observability, limited or no communication, sparse and d…
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…
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…
Accelerating Training in Pommerman with Imitation and Reinforcement Learning
Hardik Meisheri, Omkar Shelke, Richa Verma +1
The Pommerman simulation was recently developed to mimic the classic Japanese game Bomberman, and focuses on competitive gameplay in a multi-agent setting. We focus on the 2$\times…
Characterizing behavioral trends in a community driven discussion platform
Sachin Thukral, Arnab Chatterjee, Hardik Meisheri +4
This article presents a systematic analysis of the patterns of behavior of individuals as well as groups observed in community-driven platforms for discussion like Reddit, where us…
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems
Hardik Meisheri, Vinita Baniwal, Nazneen N Sultana +2
This paper describes a purely data-driven solution to a class of sequential decision-making problems with a large number of concurrent online decisions, with applications to comput…
Analyzing behavioral trends in community driven discussion platforms like Reddit
Sachin Thukral, Hardik Meisheri, Tushar Kataria +4
The aim of this paper is to present methods to systematically analyze individual and group behavioral patterns observed in community driven discussion platforms like Reddit where u…
Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier
Hardik Meisheri, Nagraj Ramrao, Suman Mitra
In Brain Computer Interface (BCI), data generated from Electroencephalogram (EEG) is non-stationary with low signal to noise ratio and contaminated with artifacts. Common Spatial P…