TY - GEN
T1 - Toward optimal pedagogical action patterns by means of Partially Observable Markov Decision Process
AU - Mejía-Lavalle, Manuel
AU - Victorio, Hermilo
AU - Martínez, Alicia
AU - Sidorov, Grigori
AU - Sucar, Enrique
AU - Pichardo-Lagunas, Obdulia
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Automatic pattern generation
KW - Intelligent Tutoring Systems
KW - Optimal pedagogical actions
KW - Partially Observable Markov Decision Process
KW - Statistical & structural pattern
UR - http://www.scopus.com/inward/record.url?scp=85028449794&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-62428-0_38
DO - 10.1007/978-3-319-62428-0_38
M3 - Contribución a la conferencia
SN - 9783319624273
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 473
EP - 480
BT - Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings
A2 - Pichardo-Lagunas, Obdulia
A2 - Miranda-Jimenez, Sabino
PB - Springer Verlag
T2 - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016
Y2 - 23 October 2016 through 28 October 2016
ER -