%0 Thesis %1 Channon:masters %A Channon, Alastair D. %C UK %D 1996 %K Artificial Development, Emergence, Fractals, Intelligence, Life, Lindenmayer Modularity, Networks, Neural Recurrence Systems, algorithms, genetic programming, %T The Evolutionary Emergence route to Artificial Intelligence %U http://www.channon.net/alastair/msc/adc_msc.pdf %X The artificial evolution of intelligence is discussed with respect to current methods. An argument for withdrawal of the traditional �fitness function� in genetic algorithms is given on the grounds that this would better enable the emergence of intelligence, necessary because we cannot specify what intelligence is. A modular developmental system is constructed to aid the evolution of neural structures and a simple virtual world with many of the properties believed beneficial is set up to test these ideas. Resulting emergent properties are given, along with a brief discussion.

@mastersthesis{Channon:masters, abstract = {The artificial evolution of intelligence is discussed with respect to current methods. An argument for withdrawal of the traditional �fitness function� in genetic algorithms is given on the grounds that this would better enable the emergence of intelligence, necessary because we cannot specify what intelligence is. A modular developmental system is constructed to aid the evolution of neural structures and a simple virtual world with many of the properties believed beneficial is set up to test these ideas. Resulting emergent properties are given, along with a brief discussion.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {UK}, author = {Channon, Alastair D.}, biburl = {https://www.bibsonomy.org/bibtex/229ca4dc67134c4cd09f94eab4034153a/brazovayeye}, interhash = {e958e9ede45639a7361802ce769e1158}, intrahash = {29ca4dc67134c4cd09f94eab4034153a}, keywords = {Artificial Development, Emergence, Fractals, Intelligence, Life, Lindenmayer Modularity, Networks, Neural Recurrence Systems, algorithms, genetic programming,}, school = {School of Cognitive and Computing Sciences, University of Sussex}, size = {30 pages}, timestamp = {2008-06-19T17:37:32.000+0200}, title = {The Evolutionary Emergence route to Artificial Intelligence}, url = {http://www.channon.net/alastair/msc/adc_msc.pdf}, year = 1996 }