On agent-based software engineering
Artificial Intelligence
Brokering and matchmaking for coordination of agent societies: a survey
Coordination of Internet agents
An improvement to matchmaking algorithms for middle agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace
Autonomous Agents and Multi-Agent Systems
Impact: A Platform for Collaborating Agents
IEEE Intelligent Systems
The Vision of Autonomic Computing
Computer
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
A Multi-Agent Systems Approach to Autonomic Computing
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Autonomic computing: an overview
UPP'04 Proceedings of the 2004 international conference on Unconventional Programming Paradigms
Agent-based game-theoretic model for collaborative web services: Decision making analysis
Expert Systems with Applications: An International Journal
Electronic Commerce Research and Applications
Hi-index | 0.00 |
Agent service description and matchmaking problem for autonomic element has been taken as one of the most important issue in the field of autonomic computing based on agent and multi-agent system. Considering the semantic and QoS for capability description of agent service are two important issues during matchmaking, the factors of semantic and QoS during matchmaking are considered together, and an agent service description model named ASDM_SQ is proposed. On basis of this model, a matchmaking algorithm with semantic and QoS constraints named ASMA_SQ is presented to find the agent service satisfied both the given semantic similarity threshold and optimal QoS performance. The proposed algorithm lies over two fundamental processes: semantic similarity matchmaking and QoS matchmaking. During QoS matchmaking, evaluation mechanism of confidence of individual QoS attributes, i.e. fidelity factor is introduced to overcome drawbacks such as subjectiveness and unfairness and improve the self-configuration capability for agent element. Simulation experiments demonstrate the effective and correction of our algorithm for agent service matchmaking, and perform better QoS performance than other existing algorithm, which can further show that our algorithm has better compromise between attribute quality and users' evaluation when selecting agent service.