@inproceedings{conf/eScience/GrimmGMPGHSZ07,
	title = {Trust Issues in Shibboleth-Enabled Federated Grid Authentication and Authorization Infrastructures Supporting Multiple Grid Middleware.},
	author = {Christian Grimm and Ralf Groeper and Siegfried Makedanz and Hans Pfeiffenberger and Peter Gietz and Martin Haase and Michael Schiffers and Wolfgang Ziegler},
	booktitle = {eScience},
	crossref = {conf/eScience/2007},
	pages = {569-576},
	publisher = {IEEE Computer Society},
	url = {http://dblp.uni-trier.de/db/conf/eScience/eScience2007.html#GrimmGMPGHSZ07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2136c2ec8c5518c2964e5ef43639e06d6/dblp},
	description = {dblp},
	ee = {http://doi.ieeecomputersociety.org/10.1109/E-SCIENCE.2007.80}, date = {2008-07-14},
	keywords = {dblp }
}

@inproceedings{conf/or/NickelVZ07,
	title = {Optimal Control Strategies for Incoming Inspection.},
	author = {Stefan Nickel and Sebastian Velten and Hans-Peter Ziegler},
	booktitle = {OR},
	crossref = {conf/or/2007},
	editor = {Jörg Kalcsics and Stefan Nickel},
	pages = {43-48},
	publisher = {Springer},
	url = {http://dblp.uni-trier.de/db/conf/or/or2007.html#NickelVZ07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/22b61c7e666fb32691c3ab3af9c1076b0/dblp},
	description = {dblp},
	date = {2008-07-04}, ee = {http://dx.doi.org/10.1007/978-3-540-77903-2_7}, isbn = {978-3-540-77902-5},
	keywords = {dblp }
}

@inproceedings{conf/mc/LehelMS03,
	title = {Weblogs als ein innovatives Instrument des betrieblichen Wissensmanagements.},
	author = {Vanda Lehel and Florian Matthes and Klaus Steinfatt},
	booktitle = {Mensch & Computer},
	crossref = {conf/mc/2003},
	editor = {Gerd Szwillus and Jürgen Ziegler},
	publisher = {Teubner},
	url = {http://dblp.uni-trier.de/db/conf/mc/mc2003.html#LehelMS03},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/2d58cd723d519ce0bc41240fdee50dc6b/boehr},
	description = {Weblogs as tool for enterprise knowledge management; support Communities of Practice},
	ee = {http://mc.informatik.uni-hamburg.de/konferenzbaende/mc2003/konferenzband/muc2003-22-lehel.pdf}, date = {2005-01-20},
	keywords = {CoP blog km }
}

@article{Ziegler:2005,
	title = {Propagation Models for Trust and Distrust in Social Networks},
	address = {Hingham, MA, USA},
	author = {Cai-Nicolas Ziegler and Georg Lausen},
	journal = {Information Systems Frontiers},
	number = {4-5},
	pages = {337--358},
	publisher = {Kluwer Academic Publishers},
	url = {http://portal.acm.org/citation.cfm?id=1108451.1108466&coll=GUIDE&dl=GUIDE#},
	volume = {7},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/2dacd24132be507ae6aed87e778584f2a/gwpl},
	description = {Propagation Models for Trust and Distrust in Social Networks},
	issn = {1387-3326}, doi = {http://dx.doi.org/10.1007/s10796-005-4807-3},
	keywords = {Social_Networks distrust trust trust_propagation }
}

@inproceedings{oltean:2003:ECAL,
	title = {Evolving Evolutionary Algorithms Using Multi
                 Expression Programming},
	address = {Dortmund, Germany},
	author = {Mihai Oltean and Crina Grosan},
	booktitle = {Advances in Artificial Life. 7th European Conference
                 on Artificial Life},
	editor = {Wolfgang Banzhaf and Thomas Christaller and Peter Dittrich and Jan T. Kim and Jens Ziegler},
	month = {14-17 September},
	number = {2801},
	pages = {651--658},
	publisher = {Springer},
	series = {Lecture Notes in Artificial Intelligence},
	url = {http://springerlink.metapress.com/openurl.asp?genre=article&issn=0302-9743&volume=2801&spage=651},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/2535c854776696bb78f2422baa42b1e47/brazovayeye},
	abstract = {Finding the optimal parameter setting (i.e. the
                 optimal population size, the optimal mutation
                 probability, the optimal evolutionary model etc) for an
                 Evolutionary Algorithm (EA) is a difficult task.
                 Instead of evolving only the parameters of the
                 algorithm we will evolve an entire EA capable of
                 solving a particular problem. For this purpose the
                 Multi Expression Programming (MEP) technique is used.
                 Each MEP chromosome will encode multiple EAs. An
                 nongenerational EA for function optimisation is evolved
                 in this paper. Numerical experiments show the
                 effectiveness of this approach.},
	size = {8 pages}, email = {moltean@cs.ubbcluj.ro}, isbn = {3-540-20057-6}, notes = {ECAL-2003 Also available at www.eea.cs.ubbcluj.ro}, doi = {doi:10.1007/b12035},
	keywords = {algorithms, genetic programming }
}

@inproceedings{ecal2003,
	title = {Evolving Developmental Programs for Adaptation,
                 Morphogenesis, and Self-Repair},
	address = {Dortmund, Germany},
	author = {Julian F. Miller},
	booktitle = {Advances in Artificial Life. 7th European Conference
                 on Artificial Life},
	editor = {Wolfgang Banzhaf and Thomas Christaller and Peter Dittrich and Jan T. Kim and Jens Ziegler},
	month = {14-17 September},
	pages = {256--265},
	publisher = {Springer},
	series = {Lecture Notes in Artificial Intelligence},
	url = {http://www.elec.york.ac.uk/intsys/users/jfm7/ecal2003.pdf},
	volume = {2801},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/2f5dc2eae93389c658bc04d2b42d83b09/brazovayeye},
	abstract = {A method for evolving a developmental program inside a
                 cell to create multicellular organisms of arbitrary
                 size and characteristics is described. The cell
                 genotype is evolved so that the organism will organise
                 itself into well defined patterns of differentiated
                 cell types (e.g. the French Flag). In addition the cell
                 genotypes are evolved to respond appropriately to
                 environmental signals that cause metamorphosis of the
                 whole organism. A number of experiments are described
                 that show that the organisms exhibit emergent
                 properties of self-repair and adaptation.},
	isbn = {3-540-20057-6}, notes = {ECAL-2003 http://www.ecal2003.org/}, doi = {doi:10.1007/b12035},
	keywords = {algorithms, genetic programming }
}

@phdthesis{oai:eldorado:0x00070350,
	title = {Evolution von Laufrobotersteuerungen mit Genetischer
                 Programmierung},
	address = {Germany},
	annote = {Fachbereich 4; Universit{\"a}t Dortmund},
	author = {Jens Ziegler},
	month = {June~18},
	school = {Dortmund University},
	url = {https://eldorado.uni-dortmund.de/bitstream/2003/2743/1/Zieglerunt.pdf},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/284c57fc0b39866526b75ae989e2e4648/brazovayeye},
	abstract = {Die Evolution von Laufrobotersteuerungen mit
                 Genetischer Programmierung wird anhandunterschiedlicher
                 Roboterarchitekturen sowohl in der Simulation als auch
                 mit realen Roboternuntersucht. Bedingt durch die lang
                 andauernden Auswertungen von Laufprogrammen in
                 Simulationund Realit{\"a}t werden die Methoden der
                 Evolution - Evaluation, Selektion und Variation
                 zus{\"a}tzlicheiner gr{\"u}ndlichen Analyse unterzogen,
                 um den evolution{\"a}ren Prozess zur automatischen
                 Generierungvon optimierten Laufrobotersteuerungen
                 m{\"o}glichst zu beschleunigen.Im ersten Teil der
                 Arbeit werden Grundlagen der Evolution von
                 Laufroboterprogrammen erl{\"a}utert. InKapitel 1 wird
                 die Thematik der autonomen mobilen Roboter eingehend
                 betrachtet, wobei dasTeilgebiet der Laufroboter und die
                 speziell hierf{\"u}r relevanten Problemstellungen
                 dargestellt werden.Das zweite Kapitel besch{\"a}ftigt
                 sich mit der Genetischen Programmierung, einem
                 Spezialfall derEvolution{\"a}ren Algorithmen. Die
                 f{\"u}r die Arbeit ben{\"o}tigten Begriffe des
                 evolution{\"a}ren Rechnens werdenvereinbart, sowie die
                 grundlegenden Mechanismen evolution{\"a}rer Algorithmen
                 aufgezeigt. Hierbei wirddetailliert auf die besonderen
                 Eigenschaften der Genetischen Programmierung
                 eingegangen. Im drittenKapitel werden die
                 mathematischen Grundlagen der Dynamiksimulation von
                 Laufrobotern -Kinematik, Dynamik, Kollisionserkennung -
                 dargestellt.Der zweite Teil der Arbeit f{\"u}hrt in die
                 Thematik der Evolution von Laufrobotersteuerungen ein.
                 InKapitel 4 werden detailliert die generelle
                 Zielsetzung und die verwendeten Methoden bei der
                 Evolutionvon Robotersteuerungen beschrieben. Es wird
                 hierbei besonders die Repr{\"a}sentation
                 vonKontrollstrukturen autonomer Roboter in
                 Evolution{\"a}ren Algorithmen und die Umsetzung auf
                 reale odersimulierte Roboter diskutiert.
                 Anschlie{\ss}end wird die Methodik f{\"u}r die
                 Evolution vonLaufroboterprogrammen mit Genetischer
                 Programmierung eingef{\"u}hrt. Die Notwendigkeit
                 derEvolution mit simulierten und realen Robotern, sowie
                 die M{\"o}glichkeit, beide Alternativen gleichzeitigzu
                 verwenden, wird diskutiert.In Teil III der Arbeit
                 werden die Experimente zur Evolution von Laufprogrammen
                 pr{\"a}sentiert. InKapitel 7 wird das Laufzeitverhalten
                 der Evolution von Laufroboterprogrammen untersucht.
                 Kapitel 8zeigt die erfolgreiche Evolution von
                 Laufprogrammen f{\"u}r eine Vielfalt von Roboterformen
                 in derSimulation auf. Die Angabe eines
                 G{\"u}tekriteriums ist essenziell f{\"u}r die Evolution
                 von Laufmustern undwird eingehend diskutiert.
                 Dargestellt werden die Auswirkungen verschiedener
                 Varianten derFitnessfunktion auf die resultierenden
                 Bewegungsmuster der Roboter. Im Kapitel 9 werden
                 f{\"u}r einensowohl real als auch als Computermodell
                 existierenden humanoiden Roboter
                 Laufprogrammeevolviert. Die Ergebnisse von
                 Evolutionsl{\"a}ufen mit vierbeinigen Laufrobotern
                 werden in Kapitel 10vorgestellt. Die Resultate der
                 Experimente unter Einbeziehung der interaktiven
                 Evolution und derModellierung der Fitnessfunktion
                 zeigen eine deutliche Verbesserung gegen{\"u}ber
                 demStandardalgorithmus.},
	rights = {These documents can be used freely according to
                 copyright laws. They can be printed freely. It is not
                 allowed to distribute them further on.}, size = {182 pages}, contributor = {Prof. Dr. rer.-nat. Wolfgang Banzhaf and Fachbereich 4
                 and Prof. Dr. Heinrich M{\"u}ller}, oai = {oai:eldorado:0x00070350}, language = {GER}, notes = {sony aibo, hexapod},
	keywords = {Autonome Computational Evolution, Laufroboter, Roboter, Simulation algorithms, genetic intelligence, programming, }
}

@inproceedings{ziegler03,
	title = {Decreasing the Number of Evaluations in Evolutionary
                 Algorithms by using a Meta-Model of the Fitness
                 Function},
	address = {Essex},
	author = {Jens Ziegler and Wolfgang Banzhaf},
	booktitle = {Genetic Programming, Proceedings of EuroGP'2003},
	editor = {Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa},
	month = {14-16 April},
	pages = {264--275},
	publisher = {Springer-Verlag},
	series = {LNCS},
	url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=264},
	volume = {2610},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/21b918c7cc1e460d1fd7d8b470f99bb99/brazovayeye},
	abstract = {In this paper a method is presented that decreases the
                 necessary number of evaluations in Evolutionary
                 Algorithms. A classifier with confidence information is
                 evolved to replace time consuming evaluations during
                 tournament selection. Experimental analysis of a
                 mathematical example and the application of the method
                 to the problem of evolving walking patterns for
                 quadruped robots show the potential of the presented
                 approach.},
	organisation = {EvoNet}, publisher_address = {Berlin}, isbn = {3-540-00971-X}, notes = {EuroGP'2003 held in conjunction with EvoWorkshops
                 2003},
	keywords = {algorithms, genetic programming }
}

@inproceedings{Ebner:2003:ECAL,
	title = {Evolution and Growth of Virtual Plants},
	address = {Dortmund, Germany},
	author = {Marc Ebner},
	booktitle = {Advances in Artificial Life. 7th European Conference
                 on Artificial Life},
	editor = {Wolfgang Banzhaf and Thomas Christaller and Peter Dittrich and Jan T. Kim and Jens Ziegler},
	month = {14-17 September},
	pages = {228--237},
	publisher = {Springer},
	series = {Lecture Notes in Artificial Intelligence},
	url = {http://springerlink.metapress.com/openurl.asp?genre=article&issn=0302-9743&volume=2801&spage=228},
	volume = {2801},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/2af9ed234c22d82ebf86b73ff37b0eebf/brazovayeye},
	abstract = {According to the Red Queen hypothesis, an evolving
                 population may be improving some trait, even though its
                 fitness remains constant. We have created such a
                 scenario with a population of coevolving plants. Plants
                 are modelled using Lindenmayer systems and rendered
                 with OpenGL. The plants consist of branches and leaves.
                 Their reproductive success depends on their ability to
                 catch sunlight as well as their structural complexity.
                 All plants are evaluated inside the same environment,
                 which means that one plant is able to cover other
                 plants leaves. Leaves which are placed in the shadow of
                 other plants do not catch any sunlight. The shape of
                 the plant also determines the area where offspring can
                 be placed. Offspring can only be placed in the vicinity
                 of a plant. A number of experiments were performed in
                 different environments. The Red Queen effect was seen
                 in all cases.},
	isbn = {3-540-20057-6}, notes = {ECAL-2003}, doi = {DOI:10.1007/b12035},
	keywords = {L-systems, algorithms, co-evolution genetic plants, programming, virtual }
}

@article{Dittrich:2001:AL,
	title = {Artificial Chemistries -- {A} Review},
	author = {Peter Dittrich and Jens Ziegler and Wolfgang Banzhaf},
	journal = {Artificial Life},
	month = {Summer},
	number = {3},
	pages = {225--275},
	volume = {7},
	year = {2001},
	biburl = {http://www.bibsonomy.org/bibtex/2a52a07b60a7dbb46323b31f1776f674b/brazovayeye},
	abstract = {This article reviews the growing body of scientific
                 work in artificial chemistry. First, common motivations
                 and fundamental concepts are introduced. Second,
                 current research activities are discussed along three
                 application dimensions: modelling, information
                 processing, and optimization. Finally, common phenomena
                 among the different systems are summarized. It is
                 argued here that artificial chemistries are {"}the
                 right stuff{"} for the study of prebiotic and
                 biochemical evolution, and the provide a productive
                 framework for questions regarding the origin and
                 evolution of organisations in general. Furthermore,
                 artificial chemistries have a broad application range
                 of practical problems, and shown in this review.},
	doi = {doi:10.1162/106454601753238636},
	keywords = {chemical complex computing emergence, evolution, life, molecular of origin self-organisation, simulation, systems, }
}