Chairs' welcome for GECCO'17 workshop "evolution in cognition"

Even though evolution by means of natural selection is a simple process, it has resulted in the vastness of life forms that today exist and ever existed, and which include complex traits such as the cognitive capacity of humans. Having noted the potential of evolution's creative power, scientists have attempted to mimick this process through the use of Evolutionary Algorithms (EAs), an efficient and robust set of computational tools for optimization, which also offers a methodology for the generation of innovative solutions to novel problems.

[1]  Eörs Szathmáry,et al.  The Neuronal Replicator Hypothesis , 2010, Neural Computation.

[2]  G. Edelman Neural Darwinism: The Theory Of Neuronal Group Selection , 1989 .

[3]  Eörs Szathmáry,et al.  An Attractor Network-Based Model with Darwinian Dynamics , 2016, GECCO.

[4]  Kenneth O. Stanley,et al.  A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks , 2009, Artificial Life.

[5]  Kenneth O. Stanley,et al.  Quality Diversity: A New Frontier for Evolutionary Computation , 2016, Front. Robot. AI.

[6]  Kenneth O. Stanley,et al.  Abandoning Objectives: Evolution Through the Search for Novelty Alone , 2011, Evolutionary Computation.

[7]  J. Changeux,et al.  A theory of the epigenesis of neuronal networks by selective stabilization of synapses. , 1973, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Antoine Cully,et al.  Robots that can adapt like animals , 2014, Nature.

[9]  Jean-Baptiste Mouret,et al.  Illuminating search spaces by mapping elites , 2015, ArXiv.

[10]  Eörs Szathmáry,et al.  Cognitive Architecture with Evolutionary Dynamics Solves Insight Problem , 2017, Front. Psychol..

[11]  Kenneth O. Stanley,et al.  Compositional Pattern Producing Networks : A Novel Abstraction of Development , 2007 .

[12]  E. Szathmáry Toward major evolutionary transitions theory 2.0 , 2015, Proceedings of the National Academy of Sciences.

[13]  Luc Steels,et al.  Fluid construction grammar as a biological system , 2016 .

[14]  Eörs Szathmáry,et al.  The Major Transitions in Evolution , 1997 .

[15]  Eörs Szathmáry,et al.  Breeding novel solutions in the brain: a model of Darwinian neurodynamics , 2016, F1000Research.

[16]  Jean-Baptiste Mouret,et al.  Reset-free Trial-and-Error Learning for Data-Efficient Robot Damage Recovery , 2016, ArXiv.

[17]  Eörs Szathmáry,et al.  Breeding novel solutions in the brain: a model of Darwinian neurodynamics , 2016, F1000Research.

[18]  Risto Miikkulainen,et al.  Evolving Neural Networks through Augmenting Topologies , 2002, Evolutionary Computation.