A comparative illustration of AI planning-based web services composition
ACM SIGecom Exchanges
Matching independent global constraints for composite web services
Proceedings of the 17th international conference on World Wide Web
Minimum-cost delegation in service composition
Theoretical Computer Science
Rule-Based Semi Automatic Web Services Composition
SERVICES '09 Proceedings of the 2009 Congress on Services - I
An Approach for Mining Web Service Composition Patterns from Execution Logs
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Web service composition using markov decision processes
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
A survey of automated web service composition methods
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
IEEE Transactions on Neural Networks
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With the rapid development of web service technology, next generations of web service applications need to be able to predict problems, such as potential degradation scenarios, future erroneous behaviors and deviations from expected behaviors, and move towards resolving those problems not just reactively, but even proactively, i.e., before the problems occur. Service oriented applications are thus driven by the requirements that bring the concepts of decentralization, dynamism, adaptation, and automation to an extreme. In this paper, an approach is proposed that depends mainly on the concept of proactive adaptation by the use of reinforcement learning to achieve an autonomous dynamic behavior of web service composition considering potential degradation and emergence in QoS values. Experimental results show the effectiveness of the proposed approach in dynamic web service composition environments.