Autores
Sidorov Grigori
Pichardo Lagunas Obdulia
Título Toward optimal pedagogical action patterns by means of Partially Observable Markov Decision Process
Tipo Congreso
Sub-tipo Memoria
Descripción 15th Mexican International Conference on Artificial Intelligence, MICAI 2016
Resumen Good pedagogical actions are key components in all learning-teaching schemes. Automate that is an important Intelligent Tutoring Systems objective. We propose apply Partially Observable Markov Decision Process (POMDP) in order to obtain automatic and optimal pedagogical recommended action patterns in benefit of human students, in the context of Intelligent Tutoring System. To achieve that goal, we need previously create an efficient POMDP solver framework with the ability to work with real world tutoring cases. At present time, there are several Web available POMDP open tool solvers, but their capacity is limited, as experiments showed in this paper exhibit. In this work, we describe and discuss several design ideas toward obtain an efficient POMDP solver, useful in our problem domain. © Springer International Publishing AG 2017.
Observaciones DOI 10.1007/978-3-319-62428-0_38 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 10062
Lugar Cancún
País Mexico
No. de páginas 473-480
Vol. / Cap. 10062 LNAI
Inicio 2016-10-23
Fin 2016-10-28
ISBN/ISSN 9783319624273