@inproceedings{nair03a,
  author =	 {Ranjit Nair and Milind Tambe and Stacy Marsella},
  title =	 {Role allocation and reallocation in multiagent
                  teams: towards a practical analysis},
  booktitle =	 {Proceedings of the second international joint
                  conference on Autonomous agents and multiagent
                  systems},
  year =	 2003,
  pages =	 {552--559},
  location =	 {Melbourne, Australia},
  googleid = 	 {LVN_lsDfU_AJ:scholar.google.com/},
  doi =		 {10.1145/860575.860664},
  publisher =	 {ACM Press},
  abstract =	 {Despite the success of the BDI approach to agent
                  teamwork, initial role allocation (i.e. deciding
                  which agents to allocate to key roles in the team)
                  and role reallocation upon failure remain open
                  challenges. What remain missing are analysis
                  techniques to aid human developers in quantitatively
                  comparing different initial role allocations and
                  competing role reallocation algorithms. To remedy
                  this problem, this paper makes three key
                  contributions. First, the paper introduces RMTDP
                  (Role-based Multiagent Team Decision Problem), an
                  extension toMTDP [9], for quantitative evaluations
                  of role allocation and reallocation
                  approaches. Second, the paper illustrates an
                  RMTDP-based methodology for not only comparing two
                  competing algorithms for role reallocation, but also
                  for identifying the types of domains where each
                  algorithm is suboptimal, how much each algorithm can
                  be improved and at what computational cost
                  (complexity). Such algorithmic improvements are
                  identified via a new automated procedure that
                  generates a family of locally optimal policies for
                  comparative evaluations. Third, since there are
                  combinatorially many initial role allocations,
                  evaluating each in RMTDP to identify the best is
                  extremely difficult. Therefore, we introduce methods
                  to exploit task decompositions among subteams to
                  significantly prune the search space of initial role
                  allocations. We present experimental results from
                  two distinct domains.},
  keywords =     {multiagent bdi coalitions},
  url =		 {http://jmvidal.cse.sc.edu/library/nair03a.pdf},
  cluster = 	 {17317431010421330733}
}