@InProceedings{kraus03a,
  author =	 {Sarit Kraus and Onn Shehory and Gilad Taase},
  title =	 {Coalition Formation with Uncertain Heterogeneous
                  Information},
  booktitle =	 {Proceedings of the Second International Joint
                  Conference on Autonomous Agents and MultiAgent
                  Systems},
  pages =	 {1--8},
  year =	 2003,
  publisher =	 {{ACM}},
  cluster = 	 {8873105957526547713},
  abstract =	 {Coalition formation methods allow agents to join
                  together and are thus necessary in cases where tasks
                  can only be performed cooperatively by groups. This
                  is the case in the Request For Proposal (RFP)
                  domain, where some requester business agent issues
                  an RFP - a complex task comprised of sub-tasks - and
                  several service provider agents need to join
                  together to address this RFP. In such environments
                  the value of the RFP may be common knowledge,
                  however the costs that an agent incurs for
                  performing a specific sub-task are unknown to other
                  agents. Additionally, time for addressing RFPs is
                  limited. These constraints make it hard to apply
                  traditional coalition formation mechanisms, since
                  those assume complete information, and time
                  constraints are of lesser significance there.To
                  address this problem, we have developed a protocol
                  that enables agents to negotiate and form
                  coalitions, and provide them with simple heuristics
                  for choosing coalition partners. The protocol and
                  the heuristics allow the agents to form coalitions
                  in the face of time constraints and incomplete
                  information. The overall payoff of agents using our
                  heuristics is very close to an experimentally
                  measured optimal value, as our extensive
                  experimental evaluation shows.},
  url =		 {http://jmvidal.cse.sc.edu/library/kraus03a.pdf}
}