Readings in nonmonotonic reasoning
From logic programming towards multi-agent systems
Annals of Mathematics and Artificial Intelligence
Reasoning with Stratified Default Theories
LPNMR '95 Proceedings of the Third International Conference on Logic Programming and Nonmonotonic Reasoning
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Distributed Default Logic for Multi-agent System
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
A semantic importing approach to knowledge reuse from multiple ontologies
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Distributed reasoning in a peer-to-peer setting: application to the semantic web
Journal of Artificial Intelligence Research
Partition-based logical reasoning for first-order and propositional theories
Artificial Intelligence - Special volume on reformulation
Electronic Trading on Electricity Markets within a Multi-agent Framework
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Combining OWL ontologies using E-Connections
Web Semantics: Science, Services and Agents on the World Wide Web
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
| Hi-index | 0.00 |
In a multi-agent system the sought information can often be found across various knowledge bases, which means that making early assumptions can lead to hasty conclusions. In the paper we present a formalism for distributed default reasoning to be performed by a group of agents that share knowledge in the form of a distributed default theory. The formalism is based on default transformations, which can be used to derive answers to queries in the form of defaults. Such new defaults can then be treated as intermediate results in the reasoning process. It is shown that passing messages containing transformed defaults is more informative than strict statements and enables avoiding early conclusions. Moreover, the extended reasoning features are embedded in the description logic framework.