Creative evolutionary systems
How to study artificial creativity
C&C '02 Proceedings of the 4th conference on Creativity & cognition
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Evolution Strategies with Subjective Selection
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
What''s interesting?
Niching in evolution strategies
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
How novelty search escapes the deceptive trap of learning to learn
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Niche radius adaptation in the CMA-ES niching algorithm
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Novelty and interestingness measures for design-space exploration
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In the conceptional phases of design optimization tasks it is required to find new innovative solutions to a given problem. Although evolutionary algorithms are suitable methods to this problem, the search of a wide range of the solution space in order to identify novel concepts is mainly driven by random processes and is therefore a demanding task, especially for high dimensional problems. To improve the exploration of the design space additional criteria are proposed in the presented work which do not evaluate solely the quality of a solution but give an estimation of the probability to find alternative optima. To realize these criteria, concepts of novelty and interestingness are employed. Experiments on test functions show that these novelty guided evolution strategies identify multiple optima and demonstrate a switching between states of exploration and exploitation. With this we are able to provide first steps towards an alternative search algorithm for multi-modal functions and the search during conceptual design phases.