First-order jk-clausal theories are PAC-learnable
Artificial Intelligence
Agent theories, architectures, and languages: a survey
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Logical settings for concept-learning
Artificial Intelligence
User modeling in adaptive interfaces
UM '99 Proceedings of the seventh international conference on User modeling
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
Compositional design and maintenance of broker agents
Intelligent agents and their applications
A Real-Life Experiment in Creating an Agent Marketplace
Software Agents and Soft Computing: Towards Enhancing Machine Intelligence, Concepts and Applications
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Enabling Integrative Negotiations by Adaptive Software Agents
CIA '99 Proceedings of the Third International Workshop on Cooperative Information Agents III
A Comparison of ILP and Propositional Systems on Propositional Traffic Data
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Formalization of a Cooperation Model Based on Joint Intentions
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Compositional Verification of a Multi-Agent System for One-to-Many Negotiation
Applied Intelligence
Agent-mediated electronic commerce: a survey
The Knowledge Engineering Review
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Ontology-Based Learning for Negotiation
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Building a targeted mobile advertising system for location-based services
Decision Support Systems
Exhaustive simulation of consecutive mental states of human agents
Knowledge-Based Systems
Integrating semantic Web services ranking mechanisms using a common preference model
Knowledge-Based Systems
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An important ingredient in agent-mediated electronic commerce is the presence of intelligent mediating agents that assist electronic commerce participants (e.g. individual users, other agents, organisations). These mediating agents are in principle autonomous agents that interact with their environments (e.g. other agents and web-servers) on behalf of participants who have delegated tasks to them. For mediating agents a (preference) model of participants is indispensable. In this paper, a generic mediating agent architecture is introduced. Furthermore, we discuss our view of user preference modelling and its need in agent-mediated electronic commerce. We survey the state of the art in the field of preference modelling and suggest that the preferences of electronic commerce participants can be modelled by learning from their behaviour. In particular, we employ an existing machine learning method called inductive logic programming (ILP). We argue that this method can be used by mediating agents to detect regularities in the behaviour of the involved participants and induce hypotheses about their preferences automatically. Finally, we discuss some advantages and disadvantages of using inductive logic programming as a method for learning user preferences and compare this method with other approaches.