activity
20162020
most citedSemi-globally Exponential Trajectory Tracking for a Class of Spherical Robots

17 citations · 28 across the 9 of their papers we have counts for

collaborators

11 papers

eess.SY2020

Stabilizing a spherical pendulum on a quadrotor

Aradhana Nayak, Ravi Banavar, D. H. S Maithripala

In this article we design a backstepping control law based on geometric principles to swing up a spherical pendulum mounted on a moving quadrotor. The available degrees of freedom…

cs.LG2020★ 1 cited

A Decentralized Policy with Logarithmic Regret for a Class of Multi-Agent Multi-Armed Bandit Problems with Option Unavailability Constraints and Stochastic Communication Protocols

Pathmanathan Pankayaraj, D. H. S. Maithripala, J. M. Berg

This paper considers a multi-armed bandit (MAB) problem in which multiple mobile agents receive rewards by sampling from a collection of spatially dispersed stochastic processes, c…

cs.LG2019★ 1 cited

A Decentralized Communication Policy for Multi Agent Multi Armed Bandit Problems

Pathmanathan Pankayaraj, D. H. S. Maithripala

This paper proposes a novel policy for a group of agents to, individually as well as collectively, solve a multi armed bandit (MAB) problem. The policy relies solely on the informa…

eess.SY2019★ 3 cited

A bundle framework for observer design on smooth manifolds with symmetry

Anant A. Joshi, D. H. S. Maithripala, Ravi N. Banavar

The article presents a bundle framework for nonlinear observer design on a manifold with a Lie group action. The group action on the manifold decomposes the manifold to a quotient…

math.OC2019

Heterogeneous Stochastic Interactions for Multiple Agents in a Multi-armed Bandit Problem

Udari Madhushani, Naomi Ehrich Leonard

We define and analyze a multi-agent multi-armed bandit problem in which decision-making agents can observe the choices and rewards of their neighbors. Neighbors are defined by a ne…

cs.LG2017

Asymptotic Allocation Rules for a Class of Dynamic Multi-armed Bandit Problems

T. W. U. Madhushani, D. H. S. Maithripala, N. E. Leonard

This paper presents a class of Dynamic Multi-Armed Bandit problems where the reward can be modeled as the noisy output of a time varying linear stochastic dynamic system that satis…