The world of Explainable AI is rapidly expanding in scope from classification tasks to more complex decision-making processes where automated algorithms play an outsized role. The International Workshop of Explainable AI Planning (XAIP) brings together the latest and best in the field of explainable planning and sequential decision-making. The workshop is collocated with ICAPS, the premier conference on automated planning and scheduling.
Invited speakers for this year includes Dr. Been Kim (Google) and Dr.Steve Chien (JPL) !!!
Find out more: https://ibm.biz/xaip2021
Like last year, in addition to the core XAIP topics, we welcome submissions on user interfaces in XAIP, acknowledging the inseparable role of interfacing in explanations. We invite submissions of the following types relevant to the topics listed below.
Full technical papers making an original contribution; up to 9 pages including references.
Short technical papers making an original contribution; up to 5 pages including references.
Position papers proposing XAIP challenges, outlining XAIP ideas, debating issues relevant to XAIP; up to 5 pages including references.
Topics Include but are not limited to
Core XAIP
Representation, organization, and memory content used in explanation
The creation of such content during plan generation or understanding
Generation and evaluation of explanations
Contrastive explanations
The way in which explanations are communicated and personalized to humans (e.g., plan summaries, answers to questions)
The role of knowledge and learning in explainable planners
Human vs AI models in explanations
Links between explainable planning and other disciplines (e.g., social science, argumentation)
Use cases and applications of explainable planning
Ethical quandaries in explainable automated planning and scheduling
User interfaces for explainable automated planning and scheduling
Plan and schedule visualization
Mixed initiative planning and scheduling
Emerging technology for human-planner interaction
Metrics for human readability or comprehensibility of plans and schedules
Explainable automated planning and scheduling for user interfaces
Representing and solving planning domains for user interface creation and design tasks
Plan, activity, and intent recognition of users’ interactions with interfaces
Developing user (mental) models with description languages and decision processes
Submissions can be made at Openreview at the link : https://openreview.net/group?id=icaps-conference.org/ICAPS/2021/Workshop/XAIP
Submission Deadline : May 31 UTC-12
Author Notification: June 30 UTC-12
Camera Ready Deadline: TBD UTC-12
ICAPS 2020 Workshops: August 2 - 6 (Exact date TBD)
Tathagata Chakraborti | IBM Research AI
Rebecca Eifler | Saarland University
Joerg Hoffmann | Saarland University
Benjamin Krarup | King’s College London
Alan Lindsay | Heriot-Watt University
Sarath Sreedharan | Arizona State University
Silvia Tulli | Técnico
Stylianos Loukas Vasileiou | Washington University