IJCAI 2020poster0 citations
The Emerging Landscape of Explainable Automated Planning & Decision Making
Tathagata Chakraborti, Sarath Sreedharan, Subbarao Kambhampati
Abstract
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 and contrast that with earlier efforts in the field in terms of techniques, target users, and delivery mechanisms. We hope that the survey will provide guidance to new researchers in automated planning towards the role of explanations in the effective design of human-in-the-loop systems, as well as provide the established researcher with some perspective on the evolution of the exciting world of explainable planning.
Safe, Explainable, and Trustworthy AI: generalHuman aspects in AI: generalPlanning and Scheduling: general
BibTeX
@inproceedings{ijcai2020p669,
title = {The Emerging Landscape of Explainable Automated Planning & Decision Making},
author = {Chakraborti, Tathagata and Sreedharan, Sarath and Kambhampati, Subbarao},
booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
Artificial Intelligence, {IJCAI-20}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Christian Bessiere},
pages = {4803--4811},
year = {2020},
month = {7},
note = {Survey track},
doi = {10.24963/ijcai.2020/669},
url = {https://doi.org/10.24963/ijcai.2020/669},
}