@incollection{DachwaldOhndorf2019,
  author    = {Dachwald, Bernd and Ohndorf, Andreas},
  title     = {Global optimization of continuous-thrust trajectories using evolutionary neurocontrol},
  series = {Modeling and Optimization in Space Engineering},
  booktitle = {Modeling and Optimization in Space Engineering},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-10501-3},
  doi       = {10.1007/978-3-030-10501-3_2},
  pages     = {33 -- 57},
  year      = {2019},
  abstract  = {Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.},
  language  = {en}
}
@incollection{BosseBarnat2019,
  author    = {Bosse, Elke and Barnat, Miriam},
  title     = {Kombination quantitativer und qualitativer Methoden zur Untersuchung der Studieneingangsphase},
  series = {Hochschulbildungsforschung. Theoretische, methodologische und methodische Denkanst{\"o}ße f{\"u}r die Hochschuldidaktik},
  booktitle = {Hochschulbildungsforschung. Theoretische, methodologische und methodische Denkanst{\"o}ße f{\"u}r die Hochschuldidaktik},
  editor    = {Jenert, Tobias and Reinmann, Gabi and Schmohl, Tobias},
  publisher = {Springer VS},
  address   = {Wiesbaden},
  isbn      = {978-3-658-20308-5},
  pages     = {169 -- 184},
  year      = {2019},
  language  = {de}
}
@incollection{BarnatJaensch2019,
  author    = {Barnat, Miriam and J{\"a}nsch, Vanessa K.},
  title     = {Forschendes Lernen und Studienerfolg: Die Bedeutung epistemischer Neugier},
  series = {Forschendes Lernen in der Studieneingangsphase: Empirische Befunde, Fallbeispiele und individuelle Perspektiven},
  booktitle = {Forschendes Lernen in der Studieneingangsphase: Empirische Befunde, Fallbeispiele und individuelle Perspektiven},
  publisher = {Springer VS},
  address   = {Wiesbaden},
  isbn      = {978-3-658-25312-7},
  doi       = {10.1007/978-3-658-25312-7_6},
  pages     = {99 -- 109},
  year      = {2019},
  abstract  = {Forschendes Lernen ist dazu geeignet, epistemische Neugier - definiert als Freude an neuen Erkenntnissen - anzuregen und zu befriedigen. Neben der Selbstwirksamkeit zeigt sich die Neugier als relevant f{\"u}r den Studienerfolg. Allerdings ist bisher nicht gekl{\"a}rt, in welcher Beziehung diese beiden Konstrukte zueinanderstehen.},
  language  = {de}
}