72 citations · 73 across the 5 of their papers we have counts for
8 papers
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions
David Venuto, Jhelum Chakravorty, Leonard Boussioux +3
Explicit engineering of reward functions for given environments has been a major hindrance to reinforcement learning methods. While Inverse Reinforcement Learning (IRL) is a soluti…
Option-Critic in Cooperative Multi-agent Systems
Jhelum Chakravorty, Nadeem Ward, Julien Roy +4
In this paper, we investigate learning temporal abstractions in cooperative multi-agent systems, using the options framework (Sutton et al, 1999). First, we address the planning pr…
Avoidance Learning Using Observational Reinforcement Learning
David Venuto, Leonard Boussioux, Junhao Wang +4
Imitation learning seeks to learn an expert policy from sampled demonstrations. However, in the real world, it is often difficult to find a perfect expert and avoiding dangerous be…
Remote estimation over a packet-drop channel with Markovian state
Jhelum Chakravorty, Aditya Mahajan
We investigate a remote estimation problem in which a transmitter observes a Markov source and chooses the power level to transmit it over a time-varying packet-drop channel. The c…
Sufficient conditions for the value function and optimal strategy to be even and quasi-convex
Jhelum Chakravorty, Aditya Mahajan
Sufficient conditions are identified under which the value function and the optimal strategy of a Markov decision process (MDP) are even and quasi-convex in the state. The key idea…
Structure of optimal strategies for remote estimation over Gilbert-Elliott channel with feedback
Jhelum Chakravorty, Aditya Mahajan
We investigate remote estimation over a Gilbert-Elliot channel with feedback. We assume that the channel state is observed by the receiver and fed back to the transmitter with one…
Fundamental limits of remote estimation of autoregressive Markov processes under communication constraints
Jhelum Chakravorty, Aditya Mahajan
The fundamental limits of remote estimation of Markov processes under communication constraints are presented. The remote estimation system consists of a sensor and an estimator. T…
Distortion-transmission trade-off in real-time transmission of Markov sources
Jhelum Chakravorty, Aditya Mahajan
The problem of optimal real-time transmission of a Markov source under constraints on the expected number of transmissions is considered, both for the discounted and long term aver…