Solving Clustered Oversubscription Problems for Planning e-Courses

In a general setting, oversubscription in planning can be posed as: given a set of goals, each one with a utility, obtain a plan that achieves some (or all) the goals, maximizing the utility, as well as minimizing the cost of achieving those goals. In this paper, we present an application domain, automatic generation of e-learning courses design, that shows a variation of the oversubscription problem. Here, there is only one goal: generating a course design for a given student. However, in order to achieve the goal, the course design can include or not different kinds of activities, each one with a utility and cost. Furthermore, these activities are grouped into clusters, so that at least one of the activities in each cluster is needed, though many more can be used. Finally, these problems also have an overall cost threshold (usually in terms of student time). So we show several techniques for solving the clustered-oversubscription problem and their impact on planning.

[1]  Austin Tate,et al.  O-Plan: control in the open planning architecture , 1986 .

[2]  Richard M. Felder,et al.  MATTERS OF STYLE , 2004 .

[3]  Subbarao Kambhampati,et al.  Planning Graph Heuristics for Selecting Objectives in Over-subscription Planning Problems , 2005, ICAPS.

[4]  Julita Vassileva,et al.  Course sequencing techniques for large-scale web-based education , 2003 .

[5]  Olga C. Santos,et al.  Integration of Educational Specifications and Standards to Support Adaptive Learning Scenarios in ADAPTAPlan , 2008, Int. J. Comput. Sci. Appl..

[6]  Chih-Wei Hsu The SGPlan Planning System in IPC-6 , 2008 .

[7]  Michel Gendreau,et al.  Traveling Salesman Problems with Profits , 2005, Transp. Sci..

[8]  Franca Garzotto,et al.  ADAPT major design dimensions for educational adaptive hypermedia , 2004 .

[9]  David E. Smith Choosing Objectives in Over-Subscription Planning , 2004, ICAPS.

[10]  Jeroen J. G. van Merriënboer,et al.  Integrated E-Learning: Pedagogy, Technology and Organization , 2003 .

[11]  Eva Onaindia,et al.  Automatic generation of temporal planning domains for e-learning problems , 2010, J. Sched..

[12]  Raquel Fuentetaja,et al.  A Look-Ahead B&B Search for Cost-Based Planning , 2009, CAEPIA.

[13]  Eugene Fink,et al.  Integrating planning and learning: the PRODIGY architecture , 1995, J. Exp. Theor. Artif. Intell..

[14]  J. Ho,et al.  The Metric FF Planning System Translating Ignoring Delete Lists to Numeric State Variables , 2003 .