Multiagent System as an intelligent assistant tool in Sakai Diego del Blanco Orobitg Fernando Olivares Fernández UPA Universidad Politécnica de Valencia.

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Presentation transcript:

Multiagent System as an intelligent assistant tool in Sakai Diego del Blanco Orobitg Fernando Olivares Fernández UPA Universidad Politécnica de Valencia

Contents 1.Introduction 2.Example feature 3.Multi-Agent Systems 4.Example features (II) 5.Learning Style Mode considerations 6.System Architecture Personal assistants For the teacher For the student General purpose assistants 7.Web Services? 8.To do… 9.You are welcome

Introduction New ways of learning  New technologies  How can we improve an e-learning enviroment like Sakai with A.I.? Needs: Our old “Plataforma de Teleformación” –Not intelligent but offers a lot of information Users requirements –Needs of information –Nobody wants to search each time in each site for new things or urgent issues. –More dynamic help –Others…

Example feature Message: Teacher have just released a new module in “Cálculo Infinitesimal” Only for creating this simple message we need to know a lot of things: –User is on-line –List of user sites –A teacher has just created a module in a site –User wants to know this information… –…and probably a lot of more things…

Multi-Agent Systems How to know all these things? –The basic idea is to have a lot of little “goblins” in the “underworld” listening, searching and thinking about things. –Each “goblin” have a different task. –Better than goblin we can call each one: Agent

Multi-Agent Systems –An Agent must be: Reactive, to the enviroment. Proactive, try to reach their own targets Social, to comunicate with the other Agents –Roles: Each agent have a different role: –Information Agents –Interface Agents –… –Only one Agent alone, does… nothing. So we need a team: MULTI-AGENT SYSTEMS

Multi-Agent Systems What information can we adquire with these intelligent agents… Everything You Always Wanted to Know About Sakai But Were Afraid to Ask !!!

Example features (II) Information messages: You have a new message in the message center Teacher have just released a new module in “Cálculo Infinitesimal” The user: “Manolo” wants to talk with you in the chat. … Suggestions: Remeber… next week finishes term to send “Practice 2” and you have not enter yet to see the instructions. Before doing this assignement, there are two assignements more urgent to send. Maybe is a good idea to read modules 3 and 4 because the exam will be next week and you have not readed them. …

Example features (II) Warnings: You are working for more than 4 hours. Maybe you need to rest for better performance. Eh!!! You are doing nothing for a long time… are you OK? … For teachers: You are writing a module with title “Medieval culture”. Maybe this other sites can be interesting to you: ---- (List of sites) --- The use of test & quizzes in this site could help student to assimilate the knowledge. …

Learning Style Mode considerations Objective: Give to the user the best learning path and enviroment adapted to his learning capabilities. There is people that learn better with texts, other learn better with audiovisual material… with lineal path or with not orderer information... with a lot of practice or only with theory… In conclusion, each student has a different optimal way of learning. Note: For doing this we should classify contents…

System Architecture

Personal Assistant Provides help to interact with an aplication. They need: –Learn, storage and manage preferences from user and changes of these preferences. –React flexiblely to the enviroment changes. –Learn and communicate with other similar entities –User interface Agente Smit: Universitat de Girona (Spain)…

System Architecture Interface with user: Avatar Only text Sound … Interactive: Can ask user about things Preferences Agente Smit: Universitat de Girona (Spain)…

System Architecture

Learner’s Personal Assistant –Scheduler Based in Sakai’s site’s schedules, tests and tasks completed, tasks send dates… Optimize tasks ordering them with priorities and giving advices to the user about temporization. One per site but intercomunication (agents negotiation) among all the scheduler agents of the user creates a optimized complete schedule.

System Architecture Learner’s Personal Assistant –Coordinator Takes information about user preferences and store it in the “user knowledge database” –Mentor With coordinator information decides the best way for the student to tackle the study. This two agents make possible the “Learning Style Mode”

System Architecture

Teacher’s Personal Assistant –Designer Gives pedagogical advices during the developement of the sites. Can search related info in other sites or internet. –Adapter Do the tracking of the students (individual and collective) and thinks about possible adpatations of the site.

System Architecture Teacher’s Personal Assistant –Scheduler Similar at the student scheduler but information will be transferred to the Adapter agent.

System Architecture

General Purpose Assistants –Adviser (Consejero) Studies all the information that other agents are managing about the sites and the user. Decides which one is interesting and then, gives the information to the Interface Agent for display it to the user. –Wrapper The Wrapper aggent is the interface between the Multi- Agent System and Sakai. So, it traslates the questions that other agents want to know about Sakai and again translate the Sakai’s answers to the other agents.

Web Services Supposedly, Sakai can work as a XML Web Service. Wrapper Agent would use this Web Service to comunicate with Sakai. Maybe the Web Service implemented by Sakai is not enough for the wrapper “curiosity”. Then we will have to implement a new tool that gives Wrapper the complete web service we need. This will be our first task. ¿There is another way?

To do… Comunicate with Sakai –Agent Wrapper that speaks with Sakai –Probably the web service extension tool… Once done this… we can work in all the other agents.

You are welcome Any collaboration will be really appreciated. Any hint about the best way to develope the Wrapper agent will avoid us a lot of investigation work. Any comment, suggestion, critic, idea, compliments too, please at: Thanks…