Abstract
On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques.
Highlights
A major goal of the Collaborative Research Centre 901 “On-The-Fly (OTF) Computing” [1,2] is the automated composition of software services that are traded on markets and that can be flexibly combined with each other
Section 2.1), we investigate to what extent currently existing service composition techniques facilitate automatic composition of image processing solutions and how to overcome possible shortcomings
7 Conclusion and outlook In this paper, we presented a service composition approach that integrates planning and learning for coping with functional discrepancy; a challenge that inevitably emerge when dealing with markets of composed services for users
Summary
A major goal of the Collaborative Research Centre 901 “On-The-Fly (OTF) Computing” [1,2] is the automated composition of software services that are traded on markets and that can be flexibly combined with each other. A user formulates a request for an individual software solution, receives an answer in terms of a composed service, and executes the composed service. A so-called OTF provider receives and processes a user request. The processing step mainly involves automatic composition of individual software solutions based on elementary services supplied by service providers. The OTF provider responds in terms of a composed service that provides the functionality the user specified
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