@Article{vidal03d,
  author = 	 {Jos\'{e} M. Vidal},
  title = 	 {The Effects of Cooperation on Multiagent Search in Task-Oriented Domains},
  journal = 	 {Journal of Experimental and Theoretical Artificial Intelligence},
  year = 	 2004,
  volume = 	 16,
  number = 	 1,
  pages = 	 {5--18},
  doi = 	 {10.1080/09528130410001710792},
  abstract = 	 {We study the benefits of teaming and selflessness
                  when using multiagent search to solve task-oriented
                  problems.  We start by presenting a formal framework
                  for multiagent search which, we show, forms a
                  superset of the task-oriented domain, coalition
                  formation, distributed constraint satisfaction, and
                  $NK$ landscape search problems. We focus on
                  task-oriented domain problems and show how the
                  benefits of teaming and selflessness arise in this
                  domain. These experimental results are compared to
                  similar results in the $NK$ domain---from which we
                  import a predictive technique.  Namely, we show that
                  better allocations are found when the dynamics of
                  the multiagent system lie between order and
                  chaos. Several other specific findings are presented
                  such as the fact that neither absolute selfishness
                  nor absolute selflessness result in better
                  allocations, and the fact that the formation of
                  small teams usually leads to better allocations.},
  googleid = 	 {Z01pAiXjet4J:scholar.google.com/},
  url = 	 {http://jmvidal.cse.sc.edu/papers/vidal03d.pdf},
  keywords = 	 {multiagent negotiation},
  cluster = 	 {16031375571672452455}
}