3 citations · 7 across the 12 of their papers we have counts for
12 papers
Designing Effective Human-Swarm Interaction Interfaces: Insights from a User Study on Task Performance
Wasura D. Wattearachchi, Erandi Lakshika, Kathryn Kasmarik +1
In this paper, we present a systematic method of design for human-swarm interaction interfaces, combining theoretical insights with empirical evaluation. We first derived ten desig…
A Study on Human-Swarm Interaction: A Framework for Assessing Situation Awareness and Task Performance
Wasura D. Wattearachchi, Erandi Lakshika, Kathryn Kasmarik +1
This paper introduces a framework for human swarm interaction studies that measures situation awareness in dynamic environments. A tablet-based interface was developed for a user s…
Active Sensing Strategy: Multi-Modal, Multi-Robot Source Localization and Mapping in Real-World Settings with Fixed One-Way Switching
Vu Phi Tran, Asanka G. Perera, Matthew A. Garratt +2
This paper introduces a state-machine model for a multi-modal, multi-robot environmental sensing algorithm tailored to dynamic real-world settings. The algorithm uniquely combines…
Radio Source Localization using Sparse Signal Measurements from Uncrewed Ground Vehicles
Asanka Perera, Vu Phi Tran, Sreenatha Anavatti +2
Radio source localization can benefit many fields, including wireless communications, radar, radio astronomy, wireless sensor networks, positioning systems, and surveillance system…
A Robust Policy Bootstrapping Algorithm for Multi-objective Reinforcement Learning in Non-stationary Environments
Sherif Abdelfattah, Kathryn Kasmarik, Jiankun Hu
Multi-objective Markov decision processes are a special kind of multi-objective optimization problem that involves sequential decision making while satisfying the Markov property o…
Coverage Path Planning with Budget Constraints for Multiple Unmanned Ground Vehicles
Vu Phi Tran, Asanka Perera, Matthew A. Garratt +2
This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms…
Fusing Interpretable Knowledge of Neural Network Learning Agents For Swarm-Guidance
Duy Tung Nguyen, Kathryn Kasmarik, Hussein Abbass
Neural-based learning agents make decisions using internal artificial neural networks. In certain situations, it becomes pertinent that this knowledge is re-interpreted in a friend…
Frontier-led Swarming: Robust Multi-Robot Coverage of Unknown Environments
Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik +1
This paper proposes a novel swarm-based control algorithm for exploration and coverage of unknown environments, while maintaining a formation that permits short-range communication…
Q-Learning with Differential Entropy of Q-Tables
Tung D. Nguyen, Kathryn E. Kasmarik, Hussein A. Abbass
It is well-known that information loss can occur in the classic and simple Q-learning algorithm. Entropy-based policy search methods were introduced to replace Q-learning and to de…
Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding
Hung The Nguyen, Tung Duy Nguyen, Vu Phi Tran +5
The control and guidance of multi-robots (swarm) is a non-trivial problem due to the complexity inherent in the coupled interaction among the group. Whether the swarm is cooperativ…
Towards Interpretable ANNs: An Exact Transformation to Multi-Class Multivariate Decision Trees
Duy T. Nguyen, Kathryn E. Kasmarik, Hussein A. Abbass
On the one hand, artificial neural networks (ANNs) are commonly labelled as black-boxes, lacking interpretability; an issue that hinders human understanding of ANNs' behaviors. A n…
Apprenticeship Bootstrapping Via Deep Learning with a Safety Net for UAV-UGV Interaction
Hung Nguyen, Vu Tran, Tung Nguyen +5
In apprenticeship learning (AL), agents learn by watching or acquiring human demonstrations on some tasks of interest. However, the lack of human demonstrations in novel tasks wher…