Intelligent agents for educational computer-aided systems
Journal of Interactive Learning Research - Special issue on intelligent agents for educational computer-aided systems
A multi-agent system for computer science education
Proceedings of the 5th annual SIGCSE/SIGCUE ITiCSEconference on Innovation and technology in computer science education
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Logical Preference Representation and Combinatorial Vote
Annals of Mathematics and Artificial Intelligence
Information Sciences: an International Journal
Winner determination in combinatorial auctions with logic-based bidding languages
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
An Introduction to MultiAgent Systems
An Introduction to MultiAgent Systems
Comparing multiagent systems research in combinatorial auctions and voting
Annals of Mathematics and Artificial Intelligence
A Voting-Based Agent System for Course Selection in E-Learning
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
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A major potential of agent technologies is the ability to support personalized learning. This is a trend where students are taking more control of their learning in the form of personal choice over topics, activities and tools. In this context, in previous work we presented a multiagent system based on an iterative voting protocol where student agents could vote to decide which courses the university would be running, those courses with little to no interest would be cancelled. This work assumed that the preferences for different courses were independent, which is not always realistic. In this paper, we extend this work and consider complex preferences. In particular, we assume substitutable and complementary preferences between courses. We show that, by using an intelligent voting strategy which tries to predict the voting result, and takes into account the interdependencies between the courses can outperform more naive strategies.