Foundations of statistical natural language processing
Foundations of statistical natural language processing
Comparing the performance of database selection algorithms
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A Multi-Agent Policy-Gradient Approach to Network Routing
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Multi-Agent Approach for Peer-to-Peer Based Information Retrieval System
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
A Dynamically Formed Hierarchical Agent Organization for a Distributed Content Sharing System
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
User modeling for full-text federated search in peer-to-peer networks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-agent based peer-to-peer information retrieval systems with concurrent search sessions
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Learning the task allocation game
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Ants and reinforcement learning: a case study in routing in dynamic networks
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Federated search of text-based digital libraries in hierarchical peer-to-peer networks
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Searching and sharing information in networks of heterogeneous agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Integrating organizational control into multi-agent learning
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Applying User Feedback and Query Learning Methods to Multiple Communities
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
Self-organization for coordinating decentralized reinforcement learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Information sharing and searching via collaborative reinforcement learning
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
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The dominant existing routing strategies employed in peer-to-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend on the content similarity between incoming queries and their direct neighboring agents to direct the distributed search sessions. However, such a heuristic is myopic in that the neighboring agents may not be connected to more relevant agents. In this paper, an online reinforcement-learning based approach is developed to take advantage of the dynamic run-time characteristics of P2P IR systems as represented by information about past search sessions. Specifically, agents maintain estimates on the downstream agents' abilities to provide relevant documents for incoming queries. These estimates are updated gradually by learning from the feedback information returned from previous search sessions. Based on this information, the agents derive corresponding routing policies. Thereafter, these agents route the queries based on the learned policies and update the estimates based on the new routing policies. Experimental results demonstrate that the learning algorithm improves considerably the routing performance on two test collection sets that have been used in a variety of distributed IR studies.