1. Developing Intelligent Agents and Multiagent Systems for Educational Applications Leen-Kiat Soh Department of Computer Science and Engineering University of Nebraska lksoh@cse.unl.edu

2. What is an Agent? An agent is an entity that takes sensory input from its environment, makes autonomous decisions, and carries out actions that affect the environment Environment sensory input output actions Agent think! Agents and MAS | I-MINDS | ILMDA

3. What is an Intelligent Agent? An intelligent agent is one that is capable of flexible autonomous actions in order to meet its design objectives, where flexibility means: –Reactivity, Pro-activeness and Social ability Machine Learning in AI says Not all agents are intelligent! Agents and MAS | I-MINDS | ILMDA The acquisition of new knowledge and motor and cognitive skills and the incorporation of the acquired knowledge and skills in future system activities, provided that this acquisition and incorporation is conducted by the system itself and leads to an improvement in its performance.

4. What is a Multiagent System? A multiagent system is a system where multiple agents perform a task better when working together –Interaction (communication) –Coordination –Collaboration Example: A group of basketball players who do not observe or communicate with each other is not a team—simply a group of individual agents. Agents and MAS | I-MINDS | ILMDA

5. Education Systems Not all computer-aided learning and teaching systems are agent-based, not all are intelligent Systems related to agents and multiagent systems focus on three areas: –Intelligent User Interface –Tutors –Multiagent Systems Agents and MAS | I-MINDS | ILMDA

6. Intelligent Multiagent Infrastructure for Distributed Systems in Education (I-MINDS) Agents and MAS | I-MINDS | ILMDA

7. I-MINDS: Goals To build a multiagent infrastructure for distributed systems, in an education application –To employ multiagent intelligence to facilitate teaching and learning processes –To enhance peer (or collaborative) learning among students –To loosen spatial and temporal constraints of conventional lecture delivery (for distance learning) Agents and MAS | I-MINDS | ILMDA

8. Help Teachers Teach I-MINDS helps teachers teach –Organize lectures (distance learning, e-archival) –Manage students –Keep track of classroom activities –Profile students dynamically –Rank real-time questions –Help deliver customized questions/quizzes/homework –Learn about the students –Learn about the lectures –Learn about the ranking of questions (keywords) Agents and MAS | I-MINDS | ILMDA

9. Help Students Learn I-MINDS helps students learn –Organize lectures (distance learning, e-archival) –Keep track of classroom activities –Profile students dynamically –Form “buddy group” (peer learning and real-time collaboration via forum and whiteboard) –Encourage students to ask questions and to be more proactive –Learn about forming buddy group dynamically –Learn about good questions –Learn about good answers Agents and MAS | I-MINDS | ILMDA

10. Capabilities (Intelligent Agents and MAS) Teacher Agent evaluate each (textual) question (text) based on its timestamp, content, images, quality (keyword-based), and the profile of the questioner rank audio questions based on student profile profile each student based on the number of questions asked, number of questions answered by the teacher, average length and quality of questions communicate, transmit lectures, archive, collect statistics, monitor the system Student Agent profile each student in the buddy group based on their response adaptively refine the buddy group based on the buddies’ profile communicate, transmit questions and responses, archive, collect statistics, monitor the system Agents and MAS | I-MINDS | ILMDA

11. Screenshots Agents and MAS | I-MINDS | ILMDA

12. Screenshots Agents and MAS | I-MINDS | ILMDA

13. Intelligent Learning Materials Delivery Agent (ILMDA) Agents and MAS | I-MINDS | ILMDA

14. ILMDA: Goals Build an intelligent agent with machine learning capabilities to deliver better learning materials to students –Incorporates instructional technology techniques such as adaptive quiz, learning objects, learner modeling, and so on –Investigates how agents can learn to deliver better learning materials to students –Employs sound artificial intelligence (AI) techniques case-based reasoning, reinforcement learning, dynamic profiling, semantic search, rule-based reasoning, simulated annealing Agents and MAS | I-MINDS | ILMDA

15. Design ILMDA delivers learning materials based on –The usage history of the learning materials Each Learning Material consists of a tutorial, a set of related examples, and a set of exercise problems –The student static background profile E.g., GPA, majors, interests –The student dynamic activity profile Based on their interactions with the agent Agents and MAS | I-MINDS | ILMDA

16. Assumptions Assumption 1: A student’s behavior in viewing an online tutorial, and how he or she interacts with the tutorial, the examples, and the exercises –is a good indicator of how well the student is understanding the topic in question, and –this behavior is observable and quantifiable Assumption 2: Different students exhibit different behaviors for different topics consistently enough to be recognized as patterns Agents and MAS | I-MINDS | ILMDA

17. Helps Students Learn Agents and MAS | I-MINDS | ILMDA ILMDA Reasoning student Computer & GUI database lectures Historical profile, Real-time behavior Parametric profile of student and environment Retrieval instructions Profile updates Statistics updates Timely delivery of examples & exercise problems Examples Exercise problems Statistics ILMDA Agent

18. Capabilities Front-End GUI To register students, capture student dynamic profile, deliver learning materials, To enter learning materials To enter domain expertise – heuristics, weights Intelligent Agent CBR, multi-layered learning modules, database retrieval, self-evaluation Backend Database mySQL database, multiple databases for content, expertise, profiles Agents and MAS | I-MINDS | ILMDA

19. Screenshots Agents and MAS | I-MINDS | ILMDA

20. Screenshots Agents and MAS | I-MINDS | ILMDA

21. To Probe Further http://www.cse.unl.edu/agents @