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Phase coexistence in a forecasting game | | Philippe Curty
; Matteo Marsili
; | | Rating: | Visitors: 5/5 (1 visitor) | | Date: |
17 Feb 2006 | | Subject: | Physics and Society (physics.soc-ph); Disordered Systems and Neural Networks (cond-mat.dis-nn); Adaptation and Self-Organizing Systems (nlin.AO) | | Abstract: | Individual choices are either based on personal experience or on information
provided by peers. The latter case, causes individuals to conform to the
majority in their neighborhood. Such herding behavior may be very efficient in
aggregating disperse private information, thereby revealing the optimal choice.
However if the majority relies on herding, this mechanism may dramatically fail
to aggregate correctly the information, causing the majority adopting the wrong
choice. We address these issues in a simple model of interacting agents who aim
at giving a correct forecast of a public variable, either seeking private
information or resorting to herding. As the fraction of herders increases, the
model features a phase transition beyond which a state where most agents make
the correct forecast coexists with one where most of them are wrong. Simple
strategic considerations suggest that indeed such a system of agents
self-organizes deep in the coexistence region. There, agents tend to agree much
more among themselves than with what they aim at forecasting, as found in
recent empirical studies. | | Source: | arXiv, physics/0506151 | | Services: | Forum | Review | PDF | Favorites | |
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