@techreport{kotthoff_llama:_2013,
  address = {arXiv},
  title = {{LLAMA}: {Leveraging} {Learning} to {Automatically} {Manage} {Algorithms}},
  url = {http://arxiv.org/abs/1306.1031},
  abstract = {Algorithm portfolio approaches have achieved remarkable improvements over single solvers. However, the implementation of such systems is often highly specialized and specific to the problem domain. This makes it difficult for researchers to explore different techniques for their specific problems. We present LLAMA, a modular and extensible toolkit that facilitates the exploration of a range of different portfolio techniques on any problem domain. We describe the current capabilities and limitations of the toolkit and illustrate its usage on a set of example SAT problems.},
  number = {arXiv:1306.1031},
  author = {Kotthoff, Lars},
  month = jun,
  year = {2013},
  month_numeric = {6}
}