NDLI: Tractable POMDP representations for intelligent tutoring systems

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Issue 4(Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers), September 2013

Issue 3(Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction), June 2013

Issue 2(Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems), March 2013

Introduction to the special section on agent communication

Research directions in agent communication

Formalizing and verifying protocol refinements

Constitutive and regulative specifications of commitment protocols: A decoupled approach

Introduction to special section on trust in multiagent systems

A framework for trust modeling in multiagent electronic marketplaces with buying advisors to consider varying seller behavior and the limiting of seller bids

Building and using social structures: A case study using the agent ART testbed

Stereotypical trust and bias in dynamic multiagent systems

From manifesta to krypta: The relevance of categories for trusting others

Introduction to the special section on intelligent tutoring and coaching systems

Tractable POMDP representations for intelligent tutoring systems

LONET: An interactive search network for intelligent lecture path generation

Personalized reading support for second-language web documents

Intelligent systems and technology for integrative and predictive medicine: An ACP approach

A parts-based approach for automatic 3D shape categorization using belief functions

Learning image-to-class distance metric for image classification

A fully online and unsupervised system for large and high-density area surveillance: Tracking, semantic scene learning and abnormality detection

A conformant planner based on approximation: CpA(H)

Issue 1(Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context), January 2013

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 3

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 2

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 1

Tractable POMDP representations for intelligent tutoring systems

Content Provider	ACM Digital Library
Author	Sukthankar, Gita Folsom-kovarik, Jeremiah T. Schatz, Sae
Copyright Year	2013
Abstract	With Partially Observable Markov Decision Processes (POMDPs), Intelligent Tutoring Systems (ITSs) can model individual learners from limited evidence and plan ahead despite uncertainty. However, POMDPs need appropriate representations to become tractable in ITSs that model many learner features, such as mastery of individual skills or the presence of specific misconceptions. This article describes two POMDP representations—state queues and observation chains—that take advantage of ITS task properties and let POMDPs scale to represent over 100 independent learner features. A real-world military training problem is given as one example. A human study $(\textit{n}$ = 14) provides initial validation for the model construction. Finally, evaluating the experimental representations with simulated students helps predict their impact on ITS performance. The compressed representations can model a wide range of simulated problems with instructional efficacy equal to lossless representations. With improved tractability, POMDP ITSs can accommodate more numerous or more detailed learner states and inputs.
Starting Page	1
Ending Page	22
Page Count	22
File Format	PDF
ISSN	21576904
e-ISSN	21576912
DOI	10.1145/2438653.2438664
Volume Number	4
Issue Number	2
Journal	ACM Transactions on Intelligent Systems and Technology (TIST)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-04-03
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Partially observable Markov decision processes Computer-based training Intelligent tutoring systems
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Theoretical Computer Science

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning

Complexity of finite-horizon Markov decision process problems

Approximate planning for bayesian hierarchical reinforcement learning

Tractable POMDP representations for intelligent tutoring systems

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