Stochastic Action Prediction for Imitation Learning

no code implementations • 26 Dec 2020 • Sagar Gubbi Venkatesh, Nihesh Rathod, Shishir Kolathaya, Bharadwaj Amrutur

Imitation learning is a data-driven approach to acquiring skills that relies on expert demonstrations to learn a policy that maps observations to actions.

Action Generation Imitation Learning

COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation

1 code implementation • 22 Dec 2020 • Siva Athreya, Giridhara R. Babu, Aniruddha Iyer, Mohammed Minhaas B. S., Nihesh Rathod, Sharad Shriram, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan

We provide a methodology by which an epidemiologist may arrive at an optimal design for a survey whose goal is to estimate the disease burden in a population.

Applications Optimization and Control 62K05, 62P10

City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic

1 code implementation • 11 Aug 2020 • Shubhada Agrawal, Siddharth Bhandari, Anirban Bhattacharjee, Anand Deo, Narendra M. Dixit, Prahladh Harsha, Sandeep Juneja, Poonam Kesarwani, Aditya Krishna Swamy, Preetam Patil, Nihesh Rathod, Ramprasad Saptharishi, Sharad Shriram, Piyush Srivastava, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan

We highlight the usefulness of city-scale agent-based simulators in studying various non-pharmaceutical interventions to manage an evolving pandemic.

Populations and Evolution Other Computer Science Physics and Society Quantitative Methods

COVID-19 Epidemic Study II: Phased Emergence From the Lockdown in Mumbai

1 code implementation • 5 Jun 2020 • Prahladh Harsha, Sandeep Juneja, Preetam Patil, Nihesh Rathod, Ramprasad Saptharishi, A. Y. Sarath, Sharad Sriram, Piyush Srivastava, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan

In an earlier IISc-TIFR Report, we presented an agent-based city-scale simulator(ABCS) to model the progression and spread of the infection in large metropolises like Mumbai and Bengaluru.