Personalisation for user agents

This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed in detail. Also experimental results, which indicate that a high level of personalisation can be achieved by this approach, are presented. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning—induction, knowledge acquisition; I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence—intelligent agents General Terms Algorithms, Human Factors, Design Keywords User agents, symbolic learning, personalisation

• Type: Conference
• Year: 2005
• Where: ATAL
• Authors: Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee Siong Ng
• Keywords: Artificial Intelligence, ATAL 2005, Machine Learning Techniques, User Agents