Browsing by Author "Richter, Hendrik"
Now showing items 1-5 of 5
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Hyper-learning for population-based incremental learning in dynamic environments.
Yang, Shengxiang; Richter, Hendrik (Article)The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied for dynamic optimization problems. This paper ... -
Learning behavior in abstract memory schemes for dynamic optimization problems.
Richter, Hendrik; Yang, Shengxiang (Article)Integrating memory into evolutionary algorithms is one major approach to enhance their performance in dynamic environments. An abstract memory scheme has been recently developed for evolutionary algorithms in dynamic ... -
Learning in abstract memory schemes for dynamic optimization.
Richter, Hendrik; Yang, Shengxiang (Article)We investigate an abstraction based memory scheme for evolutionary algorithms in dynamic environments. In this scheme, the abstraction of good solutions (i.e., their approximate location in the search space) is stored in ... -
Memory based on abstraction for dynamic fitness functions.
Richter, Hendrik; Yang, Shengxiang (Article)This paper proposes a memory scheme based on abstraction for evolutionary algorithms to address dynamic optimization problems. In this memory scheme, the memory does not store good solutions as themselves but as their ...