The emerging landscape of explainable ai planning and decision making

T Chakraborti, S Sreedharan… - arXiv preprint arXiv …, 2020 - arxiv.org
In this paper, we provide a comprehensive outline of the different threads of work in
Explainable AI Planning (XAIP) that has emerged as a focus area in the last couple of years …

Reinforcement learning interpretation methods: A survey

A Alharin, TN Doan, M Sartipi - IEEE Access, 2020 - ieeexplore.ieee.org
Reinforcement Learning (RL) systems achieved outstanding performance in different
domains such as Atari games, finance, healthcare, and self-driving cars. However, their …

English teaching practice based on artificial intelligence technology

Y Bin, D Mandal - Journal of Intelligent & Fuzzy Systems, 2019 - content.iospress.com
The automatic scoring of English composition is an inevitable trend of the rapid development
of computer technology and artificial intelligence technology. This makes the research on …

Event-driven temporal models for explanations-ETeMoX: explaining reinforcement learning

JM Parra-Ullauri, A García-Domínguez… - Software and Systems …, 2022 - Springer
Modern software systems are increasingly expected to show higher degrees of autonomy
and self-management to cope with uncertain and diverse situations. As a consequence …

[Retracted] IoT‐Based English Translation Teaching from the Perspective of Artificial Intelligence

D Liu - International Journal of Antennas and Propagation, 2022 - Wiley Online Library
In recent years, with the development of artificial intelligence, the Internet of Things (IoT) has
become a research hotspot in industry and academia. At the same time, as a derivative tool …

Automated quantitative image analysis of hematoxylin-eosin staining slides in lymphoma based on hierarchical Kmeans clustering

P Shi, J Zhong, R Huang, J Lin - 2016 8th International …, 2016 - ieeexplore.ieee.org
The microscopic image of tissue section stained by hematoxylin-eosin (HE) is an essential
part in histopathology researches. Automated HE image processing remains challenging …

Beyond theory and data in preference modeling: Bringing humans into the loop

TE Allen, M Chen, J Goldsmith, N Mattei… - … Decision Theory: 4th …, 2015 - Springer
Many mathematical frameworks aim at modeling human preferences, employing a number
of methods including utility functions, qualitative preference statements, constraint …

Why: Natural explanations from a robot navigator

R Korpan, SL Epstein, A Aroor, G Dekel - arXiv preprint arXiv:1709.09741, 2017 - arxiv.org
Effective collaboration between a robot and a person requires natural communication. When
a robot travels with a human companion, the robot should be able to explain its navigation …

Foundations of Human-Aware Explanations for Sequential Decision-Making Problems

S Sreedharan - 2022 - search.proquest.com
Abstract Recent breakthroughs in Artificial Intelligence (AI) have brought the dream of
developing and deploying complex AI systems that can potentially transform everyday life …

[PDF][PDF] Tarot: a course advising system for the future

J Eckroth, R Anderson - Journal of Computing Sciences in Colleges, 2019 - ccsc.org
Course advising plays an important role in a student's college experience. Uninformed
decisions about which courses to take during which semesters can cause a student to fail to …