ExPLoRAA: An Intelligent Tutoring System for Active Ageing in (Flexible) Time and Space

The “Città Educante” project aims at radically rethinking the learning experience through advanced ICT technology to enrich and innovate didactic methods and tools. Among the project results, ExPLoRAA is an Intelligent Tutoring System, specifically tailored for senior citizens, which, by integrating artificial intelligence and state-of-the-art ICT techniques, is able to support older adults during visits to cultural locations in a city. In particular, ExPLoRAA integrates both the users’ psycho-physiological aspects as well as geo-localization information and temporal constraints in the attempt to personalize the learning stimuli during the visit while favouring the concept of active ageing for the older people. After a generic introduction to the “Città Educante” project, this paper presents both ExPLoRAA as a whole and some of the underlying solutions. Specifically, the paper shows some of the choices that have been made to solve problems related to temporal flexibility, supporting the dynamic adaptation of stimuli over time while ensuring the possibility for the users to further adapt a visit according to their current feelings. The paper describes both the choices made in the current system prototype and its embodiment in a concrete scenario which, by implementing a game similar to “treasure hunt”, aims at fostering the physical and cognitive activity of the participating older people.

[1]  Rina Dechter,et al.  Constraint Processing , 1995, Lecture Notes in Computer Science.

[2]  Amedeo Cesta,et al.  New Heuristics for Timeline-Based Planning , 2015, IPS@AI*IA.

[3]  Etienne Wenger,et al.  Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge , 1987 .

[4]  Christophe Lecoutre,et al.  Constraint Networks: Techniques and Algorithms , 2009 .

[5]  Amedeo Cesta,et al.  Training Crisis Managers with PANDORA , 2012, ECAI.

[6]  K. VanLehn The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems , 2011 .

[7]  Paolo Traverso,et al.  Automated planning - theory and practice , 2004 .

[8]  Stellan Ohlsson,et al.  Some principles of intelligent tutoring , 1986 .

[9]  Amedeo Cesta,et al.  Training for crisis decision making - An approach based on plan adaptation , 2014, Knowl. Based Syst..

[10]  Rina Dechter,et al.  Temporal Constraint Networks , 1989, Artif. Intell..

[11]  Susan M. Brookhart,et al.  Gronlund's Writing Instructional Objectives , 2008 .

[12]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[13]  Nicola Muscettola,et al.  HSTS: Integrating Planning and Scheduling , 1993 .

[14]  Amedeo Cesta,et al.  Integrating Logic and Constraint Reasoning in a Timeline-Based Planner , 2015, AI*IA.

[15]  Amedeo Cesta,et al.  Using Training with Older People for Active Ageing in Time and Space , 2017, AI*AAL@AI*IA.

[16]  Amedeo Cesta,et al.  ROBIN, a Telepresence Robot to Support Older Users Monitoring and Social Inclusion: Development and Evaluation. , 2017, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[17]  Amedeo Cesta,et al.  A Tool for Managing Elderly Volunteering Activities in Small Organizations , 2017, AI*IA.

[18]  Mathijs de Weerdt,et al.  Incrementally Solving STNs by Enforcing Partial Path Consistency , 2010, ICAPS.