According to a United Nations’ report on World Population Aging (2015), the number of people in the world aged 60 or over is projected to grow to 2.1 billion by year 2050. Aging can come with various complexities and challenges, such as frailty and decline in cognitive and mental health of a person. These changes affect a person’s everyday life, resulting in decreased social participation, lack of physical activity, and vulnerability to injury and disability, that can be exacerbated by the occurrence of various acute health events, such strokes, or long term illnesses.

Assistive technology refers to any device, equipment or tool that is used to maintain, increase or improve the functional capabilities of older adults or persons with disabilities. The field of assistive technology amalgamates several multi-disciplinary areas including computer science, rehabilitation engineering, data mining, clinical studies, health care, and psychology. The idea of assistive technological solutions is to promote independent, active and healthy aging with a specific focus on older adults, especially with mild cognitive impairments.

Collecting and mining health data using assistive technology devices is a challenging task. Leveraging Artificial Intelligence (AI) techniques and building novel machine learning (ML) models is essential to make advancements in the field of aging and technology. Building AI models on health data will facilitate independent assisted living, promote healthy and active lifestyle, and manage rehabilitation routines effectively. To reason about the collected data, to classify it and to detect abnormalities, new AI tools and methods are required.

With this workshop, we will bring together researchers from different sub-fields of AI in general, agent based modelling and machine learning to identify and approach the ARIAL-related problems. We will also facilitate discussion, interaction, and comparison of approaches, methods, and ideas related to the domain of aging and technology.

In this workshop, we invite previously unpublished and novel submissions in the following areas, but not limited to:
* Methods and protocols for data collection with older adult populations .
* Techniques for continuous streaming and monitoring of health and activity data for older adults.
* Methodologies for big data and large-scale data mining.
* Data analytics and visualization techniques for healthcare data.
* Machine learning techniques to identify abnormal behaviours and coping with rare events in health care.
* Older adults-centered analysis of online behaviour, e.g. Social Media Analytics (interpreting comments, posts, ...) and understanding (e.g. depression).
* Data mining challenges such as handling missing information, dealing with mixed, imbalanced and noisy data.
* Ontology design to capture age related impairments and possible counter-actions.
* Machine Learning approaches for the analysis of ARIAL-related data coming from sensors, cameras, ambient devices or novel sensing devices (radars, thermal camera, etc).
* Multi-agent models to capture interaction between patients, care-givers and relatives to provide assistance.
* Machine Learning methods for measuring health indicators, progression of physical and cognitive health, e.g. frailty, dementia, gait stability or other decline over time.
* Probabilistic and Case-based reasoning to provide assistance.
* Using Deep Learning solutions for supporting assistive technology devices.
* Predictive models for Fall detection, Agitation detection in people living with dementia.
* Methods to detect harmful and life-threatening events in older adults such as strokes, seizures, wandering.
* Developing smart agents to understand sentiments of the client for providing focussed care.
* Developing smart-home solutions for connecting and engaging older adults with the environment.
* Models that use Speech recognition and dialog based interaction with older adults

Important Dates
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* Paper submissions: April 25, 2018
* Paper notifications: May 15, 2018
* Camera-ready deadline for the final version of accepted papers: May 25, 2018
* Workshop dates: July 13-15, 2018

Submission Guidelines
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We will accept papers in two formats:

* Short papers - 4 pages (including references).
* Extended Abstracts / Demo Papers - 2 pages (including references).

The short papers will be orally presented in the workshop. The Extended Abstract / Demo papers' authors need to prepare a poster that will be displayed during the workshop.
Submitted papers will be reviewed by at least two independent referees from the Program Committee. Submissions that do not follow the above guidelines will not be reviewed. The papers should be submitted using the IJCAI format - http://www.ijcai.org/authors_kit.

Papers can be submitted using the EasyChair portal - https://easychair.org/conferences/?conf=arialijcai2018.

Accepted papers to ARIAL will be invited to submit an extended full length paper to the Journal of Healthcare Informatics Research (JHIR - Springer) and a fast track review will be conducted. There will be opportunity for accepted authors to contribute book chapters in the CRC Book Series on Health Informatics.

***At least one author of the accepted paper needs to attend ARIAL in order to be considered for possible publication opportunity in JHIR and be included in workshop proceedings.

Workshop Co-chairs
* Alex Mihailidis, University of Toronto, Canada
* Shehroz Khan, University of Toronto and Toronto Rehabilitation Institute, Canada
* Sebastian Bader, University of Rostock, Germany

Local Area Chair
* Alexandra König, Centre Hospitalier Universitaire de Nice, France

Program Committee
* Jesse Hoey, University of Waterloo, Canada
* Thomas Ploetz, Georgia Institute of Technology, USA
* Christopher Nugent, Ulster University, UK
* Jan Alexandersson, German Research Center for Artificial Intelligence, Germany
* Babak Taati, Toronto Rehabilitation Institute, Canada
* Louise Hopper, Dublin City University, Ireland
* Yiannis Kompatsiaris, Information Technologies Institute, Greece
* Jennifer Boger, University of Waterloo, Canada
* François Brémond, INRIA Sophia Antipolis, France
* Robby Goetschalckx, Connected Signals Inc., USA
* Amir Ahmad, UAE University, Al-Ain, UAE
* Alexandra König, Centre Hospitalier Universitaire de Nice, France
* Belkacem Chikhaoui, TELUQ University, Canada
* Mohammad Mehedy Masud, UAE University, Al-Ain, UAE
* Marco Lorenzi, Université Côte d'Azur, Inria, France