@InProceedings{klos09a,
  author =	 {Tomas Klos and Bart Nooteboom},
  title =	 {Adaptive Learning in Evolving Task Allocation
                  Networks},
  booktitle =	 {Proc. of the 8th Int. Conf. on Autonomous Agents and
                  Multi-Agent Systems},
  crossref =	 {aamas09},
  pages =	 {465--472},
  year =         2009,
  abstract =	 {In this paper, we study multi-agent economic systems
                  using a recent approach to economic modeling called
                  Agent-based Computational Economics (ACE): the
                  application of the Complex Adaptive Systems (CAS)
                  paradigm to economics. In this paper, we apply the
                  CAS paradigm to the study of an industrial goods
                  market, where firms need to decide between making
                  and buying components. Computer simulations using
                  our model explain different emerging distributions
                  of economic activity among organizational forms
                  (market and hierarchy) in terms of the search
                  problem facing the agents, and in terms of the
                  negative consequences of the agents’ search behavior
                  on their perceived trustworthiness in the eyes of
                  their potential partners. A further impediment to
                  reaching optimal allocations we observe is that
                  agents learn to protect themselves and their current
                  allocation by being loyal and by focusing on their
                  trust in their partner, rather than their partner’s
                  profit generating potential.},
  url = 	 {http://jmvidal.cse.sc.edu/library/klos09a.pdf},
  keywords = 	 {task-allocation},
  cluster = 	 {9297274013094452253}
}