Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Distributed Artificial Intelligence
Distributed Artificial Intelligence
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Query processing in the SIMS information mediator
Readings in agents
Matchmaking for information services
Readings in agents
Learning in multiagent systems
Multiagent systems
Agents teaching agents to share meaning
Proceedings of the fifth international conference on Autonomous agents
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Modern Information Retrieval
A language modeling framework for resource selection and results merging
Proceedings of the eleventh international conference on Information and knowledge management
Sharing Knowledge: Starting with the Integration of Vocabularies
Proceedings of the 7th Annual Workshop on Conceptual Structures: Theory and Implementation
Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Relevant document distribution estimation method for resource selection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
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
Domain Independent Learning of Ontology Mappings
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Balancing ontological and operational factors in refining multiagent neighborhoods
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Reflective negotiating agents for real-time multisensor target tracking
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Privacy-conscious P2P data sharing scheme with bogus profile distribution
Web Intelligence and Agent Systems
On-line coordination: Event interaction and state communication between cooperative agents
Web Intelligence and Agent Systems
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Our system, based on a multiagent framework called collaborative understanding of distributed knowledge (CUDK), is designed with the overall goal of balancing agents' conceptual learning and task accomplishment. The tradeoff between the two is that while conceptual learning allows an agent to improve its own concept base, it could be counter-productive: conceptual learning is time consuming and requires processing resources necessary for the agent to accomplish its tasks. In our current phase of research, we investigate the roles of resource and knowledge constraints, environmental factors (such as the frequency of queries), and learning mechanisms in a CUDK-based distributed information retrieval (DIR) application. In this application, an agent is motivated to learn about its neighbors' concept base so it can collaborate to satisfy queries that it cannot satisfy alone. Similarly, to conserve resources, an agent is motivated not to learn from neighbors that have been unhelpful in the past. As a result, it is possible for an agent to learn from a helpful neighbor that is not the authoritative expert in the system. The agents use neighborhood profiling to learn about other agents' helpfulness and conceptual inferencing to learn about other agents' known concepts. The helpfulness measure defines a metric called collaboration utility, and the inferencing results are stored in a translation table in which each entry is a mapping between two concepts plus an associated credibility score. The experiments investigate how operational and conceptual factors impact the DIR application's performance.