Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
A multiagent system manages collaboration in emergent processes
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Trust and honour in information-based agency
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Foundations and Trends in Web Science
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Coordination and Agreement in Multi-Agent Systems
CIA '08 Proceedings of the 12th international workshop on Cooperative Information Agents XII
Coordination in Multi-Agent Systems: Towards a Technology of Agreement
MATES '08 Proceedings of the 6th German conference on Multiagent System Technologies
Intelligent ontological multi-agent for healthy diet planning
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Ontology-based information content computation
Knowledge-Based Systems
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The Semantic Web makes unique demands on agency. Such agents should: be built around an ontology and should take advantage of the relations in it, be based on a grounded approach to uncertainty, be able to deal naturally with the issue of semantic alignment, and deal with interaction in a way that is suited to the co-ordination of services. A new breed of 'information-based' intelligent agents [C. Sierra, J. Debenham, Information-based agency, in: Proceedings of Twentieth International Joint Conference on Artificial Intelligence IJCAI-07, Hyderabad, India, 2007, pp. 1513-1518.] meets these demands. This form of agency is founded on ideas from information theory, and was inspired by the insight that interaction is an information revelation and discovery process. Ontologies are fundamental to these agent's reasoning that relies on semantic distance measures. They employ entropy-based inference, a form of Bayesian inference, to manage uncertainty that they represent using probability distributions. Semantic alignment is managed through a negotiation process during which the agent's uncertain beliefs are continually revised. The co-ordination of services is achieved by modelling interaction as time-constrained, resource-constrained processes - a proven application of agent technology. In addition, measures of trust, reputation, and reliability are unified in a single model.