Improving conversation engagement through data-driven agent behavior modification

Michael Procter, Fuhua Lin, Robert Heller

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

2 Citations (Scopus)

Abstract

E-learning systems based on a conversational agent (CA) provide the basis of an intuitive, engaging interface for the student. The goal of this paper is to propose an agent-based framework for providing an improved interaction between students and CA-based e-learning applications. Our framework models both the student and the CA and uses agents to represent data sources for each. We describe an implementation of the framework based on BDI (Belief-Desire-Intention) architecture and results of initial testing.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence - 29th Canadian Conference on Artificial Intelligence, Canadian AI 2016, Proceedings
EditorsRichard Khoury, Christopher Drummond
Pages270-275
Number of pages6
DOIs
Publication statusPublished - 2016
Event29th Canadian Conference on Artificial Intelligence, AI 2016 - Victoria, Canada
Duration: 31 May 20163 Jun. 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9673
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference29th Canadian Conference on Artificial Intelligence, AI 2016
Country/TerritoryCanada
CityVictoria
Period31/05/163/06/16

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