@InProceedings{modi05a,
  author =	 {Pragnesh Jay Modi and Manuela Veloso},
  title =	 {Bumping Strategies for the Multiagent Agreement
                  Problem},
  booktitle =	 {Proceedings of the Fourth International Joint
                  Conference on Autonomous Agents and MultiAgent
                  Systems},
  crossref =	 {aamas05},
  pages =	 {390--396},
  year =	 2005,
  abstract =	 {We introduce the Multiagent Agreement Problem (MAP)
                  to represent a class of multiagent scheduling
                  problems. MAP is based on the Distributed Constraint
                  Reasoning (DCR) paradigm and requires agents to
                  choose values for variables to satisfy not only
                  their own constraints, but also equality constraints
                  with other agents. The goal is to represent problems
                  in which agents must agree on scheduling decisions,
                  for example, to agree on the start time of a
                  meeting. We investigate a challenging class of MAP
                  --- private, incremental MAP (piMAP) in which
                  agents do incremental scheduling of activities and
                  there exist privacy restrictions on information
                  exchange. We investigate a range of strategies for
                  piMAP, called ``bumping'' strategies. We empirically
                  evaluate these strategies in the domain of calendar
                  management where a personal assistant agent must
                  schedule meetings on behalf of its human user. Our
                  results show that bumping decisions based on
                  scheduling difficulty models of other agents can
                  significantly improve performance over simpler
                  bumping strategies.},
  keywords =     {multiagent dcsp scheduling},
  url = 	 {http://jmvidal.cse.sc.edu/library/modi05a.pdf},
  googleid = 	 {RDet6aePcxUJ:scholar.google.com/},
  cluster = 	 {1545737048460965700}
}