On the generality of parameter tuning in evolutionary planning
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Instance-based parameter tuning for evolutionary AI planning
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Analyzing bandit-based adaptive operator selection mechanisms
Annals of Mathematics and Artificial Intelligence
Learn-and-Optimize: a parameter tuning framework for evolutionary AI planning
EA'11 Proceedings of the 10th international conference on Artificial Evolution
Evolutionary optimization of wetlands design
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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This book is loaded with examples in which computer scientists and engineers have used evolutionary computation - programs that mimic natural evolution - to solve real problems. They aren t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won Humies - Human Competitive Results Awards - for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems.