Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Local consensus ontologies for B2B-oriented service composition
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Learning to Share Meaning in a Multi-Agent System
Autonomous Agents and Multi-Agent Systems
Automatic Fuzzy Ontology Generation for Semantic Web
IEEE Transactions on Knowledge and Data Engineering
ANEMONE: an effective minimal ontology negotiation environment
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Ontology-guided learning to improve communication between groups of agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Learning Non-Unanimous Ontology Concepts to Communicate with Groups of Agents
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
A fuzzy ontology and its application to news summarization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Large-scale cooperative task distribution on peer-to-peer networks
Web Intelligence and Agent Systems
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We present an extension to the definition of a concept in an ontology that allows an agent to simultaneously communicate with a group of agents that might have different understandings of some concepts. We also provide a way to learn such non-unanimous concepts by using a method for learning concepts from a group of teachers. The general idea of non-unanimous concepts is to use the teachers to identify the core of a concept everyone agrees on and what else at least some of the teachers think belongs into the concept. The learning agent also decides what belongs to the concept for itself and whenever it needs to communicate with a group of other agents and needs to be precise it makes use of these three concept aspects by providing additional example objects for what might be misunderstood.