The Emergence of Trust in Multi-Agent Bidding: A Computational Approach The Emergence of Trust in Multi-Agent Bidding: A Computational Approach

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@InProceedings{wu-2001a,
  author         = {D.J. Wu and Yanjun Sun},
  title          = {The Emergence of Trust in Multi-Agent Bidding: A Computational Approach},
  year           = {2001},
  publisher      = {IEEE},
  booktitle      = {Proceedings of the 34th Hawaii International Conference on System Sciences - 2001},
  pages          = {},
  read-status    = {short-list},
  annote         = {Look for this in ACM and IEEE locations},
  key            = {wu-2001a}
}

Summary

The paper pits reinforcement learners against each other and against interpretations of classic strategies where the agents play seller agents in a in a simple electricity trading market where the buying agents follow a fixed optimal contracting strategy as developed in the authors' prior work. The idea is to see if trust emerges between the sellers, which in effect is to see if the suppliers will collude to fix prices!

The paper also examines some other areas of trading, where the number of "nasty" agents varies as a proportion of the population

Stated goals:

  1. Discover if agents can discover good bidding strategies when playing repeated non-linear games where there is no equilibrium.
  2. Explore the emergence of trust and what kinds of mechanisms induce cooperation.

Buying agents are assumed to be following optimal contracting strategy according to prior paper(s) by Wu.


Key Factors

Relations to Other Work:

Problem Addressed:

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Quality

Originality is good.
Contribution/Significance is average.
Quality of organization is average.
Quality of writing is average.
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