Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Improving problem definition through interactive evolutionary computation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
The relationship between search based software engineering and predictive modeling
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
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While recent attempts to search a conceptual software engineering design search space with multi-objective evolutionary algorithms have yielded promising results, the practical application of such search-based techniques remains to be addressed. This paper reports initial findings of the application of software agents in support of an interactive, user-centered conceptual software design scenario. The supporting role of a number of single responsibility agents is described and results for a case study indicate that the application of such agents to search-based design scenarios provides efficient, high performance and effective support. The notion of interactive, joint human-computer activity appears to map well to conceptual software design scenarios: focus on superior design concepts and thence to useful and interesting designs provides a natural and effective way of narrowing the population based search. In addition, agents and the human designer appear to interact as cooperative "team players", jointly influencing the evolutionary algorithm based search. Nevertheless, challenges remain, including expanding the scale of implementation of underlying technologies to support distributed, collaborative design.