PRAIA Pedagogical Rational and Affective Inteligent Agents)
Universities
Capes-Cofecub project between UFRGS and LIG-France
Duration
2007 a 2010
Role
Collaborateur Researcher
PRAIA is an international project of cooperation between the
researchers groups PPGC/UFRGS & PIPCA/UNISINOS in Brazil and
LIG
& LIMSI in France, which has received financial founds from
Capes/Cofecub. We are interested in, with our research, responding the
following questions:
- How to model and to represent student emotions?
- How to recognize student s emotions?
- How to respond appropriately to student s emotions?
- How to develop methods and techniques to evaluate the developed methods and techniques?
In order to respond to
those questions, we defined some activities for our project, which are:
- Analyze and study the existing methods and techniques for recognizing, modeling and expressing emotions;
- Conception of new methods and techniques for recognizing, modeling and expressing emotions;
- Develop a prototype using the methods and techniques conceive by our researches groups.
This prototype is being developed
and is a multi-user (collaborative) game, since we are mainly
interested in emotions that arise between students in collaborative and
competitive pedagogical activities.
Inference of Emotions by Face
University: PIPCA - UNISINOS
Duration: 2007-2008
Role: Superviser of Undergraduate work
This work aims at developping an application that is able to
infer the users’ emotions Happiness,
Surprise, Fear, Anger, Sadness, Disgust, from their facial expression
caught by
a webcam. The emotional detection is based on FACs psychological face
coding
system and uses machine learning algorithms for the inference. The
experiments’
results show an average success rate of 60%, arriving a 90% for the
emotions
happiness and sadness.
Uma Arquitetura Independente de Domínio e Plataforma para Apresentação de Comportamentos em Agentes Pedagógicos Animados.
University PIPCA - UNISINOS
Duration 2007
Role Superviser of Undergraduate work
This work aims ate developping the architecture and the implementation
of a module responsible for the
presentation of verbal (speech) and corporal (animation) behaviors of
animated
pedagogical agents. This module is independent of domain and
application, being
able to be inserted in any educational environment apart of its
application
domain, and independent of platform, making possible that it can be
executed in
different operational systems. In this way, it was implemented as a
reactive
agent in Java (what makes it independent of platform), called Body
agent, that
communicates with the agent’s mind using the agents
communication language
FIPA-ACL. This last capacity of the agent allows it to be inserted in
other
intelligent learning environments, if they are able to communicate in
FIPA-ACL.
Availabe for download here
(contém arquivo reademe,txt com guia de
instalação)
Pat: An Animated Pedagogical Agent to Interact Affecivelly with the Student (PhD thesis)
University PGCC-UFRGS/LIG-France
Duration 2000-2004
Role PhD Student
Superviser Rosa Vicari
This work proposes an animated
pedagogical
agent, called Pat (Pedagogical and Affective Tutor), that has the role
of providing emotional support to the student:
motivating and encouraging him, making him believe in his self-ability,
and
promoting a positive mood in him, which fosters learning. This careful
support
of the agent, its affective tactics, is expressed through emotional
behaviour
and encouragement messages of the lifelike character. Due to human
social
tendency of anthropomorphising software, we believe that a software
agent can
accomplish this affective role.
In order to choose the adequate
affective
tactics, the agent should also know the student’s emotions.
The proposed agent
recognises the student’s emotions: joy/distress,
satisfaction/disappointment,
anger/gratitude, and shame, from the student’s observable
behaviour, i. e. his
actions in the interface of the educational system. The inference of
emotions
is psychologically grounded on the cognitive theory of emotions. More
specifically, we use the OCC model which is based on the cognitive
approach of
emotion and can be computationally implemented.
Due to the dynamic nature of the
student’s
affective information, we adopted a BDI approach to implement the
affective
user model and the affective diagnosis. Besides, in our work we profit
from the
reasoning capacity of the BDI approach in order for the agent to deduce
the
student’s appraisal, which allows it to infer the
student’s emotions.
Master Dissertation: Software Agents for Analysis of Collaboration in a Virtual Classroom
University PUCRS
Duration 1998-2000
Role Master Student
Superviser Flavio de Oliveira
Trends
in distance education show a growing emphasis in collaborative
learning,
stimulating students to exchange ideas and information. When the
students
interact among themselves, they feel more motivated and engaged and get
better
results in their studies. A collaborative environment, however, will
demand a
higher effort from the teacher, who will have to supervise all the
discussions
among the learners, so that they do not deviate from the intended topic
for the
lesson. Moreover, the information proceeding from the interactions
among the
students provide the teacher with insights useful for an individual
evaluation
of the students and the course. In this way, this work presents a
Multi-agent
architecture able to monitor the communication tools in a distance
learning
group. This system will analyze the discussions taking place in these
tools
(discussion list, chat and newsgroups), showing to the teacher
statistical
information (percentage of participation and number of messages) and
identifying possible associations in the interactions - topics and
subtopics
that interest the students, groups of learners that interact
intensively, etc.