By Giorgini P. (Ed), Henderson-Sellers B. (Ed), Winikoff M. (Ed)
This booklet constitutes the completely refereed post-proceedings of the fifth overseas Bi-Conference Workshop on Agent-Oriented details platforms, held in Melbourne, Australia in July 2003 at AAMAS 2003 and in Chicago, IL, united states in October 2003 at ER 2003.The revised complete papers provided have been rigorously chosen in the course of rounds of reviewing and development from a complete of 36 submissions. The papers are equipped in topical sections on details platforms and purposes; methodologies; and modeling, research, and simulation.
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Extra resources for Agent-Oriented Information Systems: 5th International BI-Conference Workshop, Aois 2003, Melbourne, Australia, July 14, 2003 and Chicago, IL, USA, October 13th, 2003, Revised Selected Papers
Harter: Intelligent Tutoring Systems with Conversational Dialogue, AI Magazine, (2001)22(4):39-51 16. Koedinger, K. , J. R. Anderson, W. H. Hadley, and M. A. Mark: Intelligent Tutoring Goes to School in the Big City, J. Artificial Intelligence in Education, (1997)8(1):30-43 17. , S. Lajoie, M. Bunzo, and G. Eggan: SHERLOCK: A Coached Practice Environment for an Electronics Troubleshooting Job, in J. H. Larkin and R. W. ) Computer Assisted Instruction and Intelligent Tutoring Systems, (1992)201-238, Hillsdale, NJ: Lawrence Erlbaum.
In essence, these components form a toolkit that agents can access to obtain information. 2 Multiagent System In our multiagent system, there are a variety of agents: student agents and teacher agents, as well as remote counterparts and group agents. A student agent solicits input from the student, monitors the student’s activity, updates teacher’s instructions at the student’s notebook and reports the student’s information to the teacher on demand. A teacher agent collects input from the student agents, monitors the teacher’s activity and corresponding students’ behaviour, performs a wide range of data analyses on students’ input such as sort- I-MINDS: An Agent-Oriented Information System 21 ing, filtering and pattern recognition, and provides decision making support to the teacher.
The initial database of rules, quizzes and exercises are provided by the teachers or educators. These teaching materials will be modified by the learning mechanism. For example, the rules used to evaluate the quality of the questions can be changed based on its utility. The evaluation mechanism assesses the students based on their responses to the exercises and the quizzes, as well as the monitored questions and actions from their student agents. Based on the profile, the teacher agent will be able to cater to each student agent with a customized set of exercises and quizzes.
Agent-Oriented Information Systems: 5th International BI-Conference Workshop, Aois 2003, Melbourne, Australia, July 14, 2003 and Chicago, IL, USA, October 13th, 2003, Revised Selected Papers by Giorgini P. (Ed), Henderson-Sellers B. (Ed), Winikoff M. (Ed)