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Evolution and Learning

Contact: Hartmut Schmeck

Project Status: completed


The first goal of this project is to establish an understanding of the interaction between evolution and ("life time") learning. Based on this, we aim at developing a system (embedded in a test environment), that exhibits "real" learning abilitiy. This learning ability is not explictly encoded, but the goal is this ability establishes itself by means of evolution. The mapping between genotype ("genetic program") and phenotyp plays a central role in this context.

Involved Persons
Jürgen Branke, Ingo Paenke, Hartmut Schmeck


from: 1 Oktober 2004
until: 30 September 2006
Funding: Honda Research Institute Europe


Honda Research Institute Europe

Research Group

Efficient Algorithms

Area of Research

Evolutionary Computing, Evolutionary Strategies, Genetic Algorithms, Softcomputing

Publications Belonging to the Project
 - book
 - incollection
 - booklet
 - proceedings
 - techreport
 - deliverable
 - manual
 - misc
 - unpublished


Ingo Paenke, Jürgen Branke, Yaochu Jin
Efficient Search for Robust Solutions by Means of Evolutionary Algorithms and Fitness Approximation
IEEE Transactions on Evolutionary Computation, 10, (4), pages 405- 420, August, 2006

Ingo Paenke, Bernhard Sendhoff, Tadeusz Kawecki
Influence of Plasticity and Learning on Evolution under Directional Selection
The American Naturalist, 170, (2), pages E47-E58, 2007

Ingo Paenke, Tadeusz Kawecki, Bernhard Sendhoff
The Influence of Learning on Evolution - A Mathematical Framework
Artificial Life, 2008

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Ingo Paenke, Tadeusz Kawecki, Bernhard Sendhoff
On the Influence of Lifetime Learning on Selection Pressure
In LM. Rocha, LS. Yaeger, MA. Bedau, D. Floreano, RL. Goldstone and A. Vespignani, Artificial Life X : Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems, pages: 500--506, MIT Press, August, 2006

Ingo Paenke, Jürgen Branke, Yaochu Jin
On the Influence of Phenotype Plasticity on Genotype Diversity
IEEE Symposium on Foundations of Computational Intelligence, pages: 33-41

Ingo Paenke, Bernhard Sendhoff, Jon Rowe, Chrisantha Fernando
On the Adaptive Disadvantage of Lamarckianism in Rapidly Changing Environments
In F. Almeida e Costa et al., Advances in Artificial Life, 9th European Conference on Artificial Life, pages: 355-364, Springer, LNCS, 4648

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Ingo Paenke
Dynamics of Evolution and Learning
Universitätsverlag Karlsruhe, Juni, 2008

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Ingo Paenke
Dynamics of Evolution and Learning
Prof. Dr. Hartmut Schmeck / Prof. Dr. Xin Yao, 2008/02/29, PhD thesis at the Universität Karlsruhe (TH), Fakultät für Wirtschaftswissenschaften

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