IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Learning to Trust: Uncovering Unobserved Multi-Period Behavioral Strategies from Observed Stage Game Actions Using Finite Automata

Listed author(s):
  • Jim Warnick


    (University of Pittsburgh)

  • Robert L. Slonim


    (Case Western Reserve University)

We introduce a methodology to infer players' unobserved multi-period strategies from their observed stage game actions in economic decision-making experiments. We use finite-state automata to model multi-period strategies by employing an algorithm that synthesizes a minimal state automaton from a sequence of inputs and outputs. The inputs and outputs are the players' and their opponents' behavior, and the automaton is the decision rule. We use this methodology to examine new experimental data from finitely and infinitely repeated trust games. We synthesize an automaton for every behavioral observation in the experiment. Although we are able to infer that over 70 unique finite-state automata strategies are used in he infinite horizon game, over 90 percent of the data may be explained by a very small number of behaviorally interpretable strategies. We find that subjects who are in a position to initiate trust use a harsh punishment strategy infrequently (when trust is not reciprocated) in early play, but learn predominantly to use this strategy over time. By contrast, players who are in a position to reciprocate trust do not learn to reciprocate (perhaps because the harsh punishment strategy does not emerge until near the end of the session). In fact, these players appear to be exhibiting "gambler's fallacy" behavior by forming incorrect subjective probabilities that the infinite game will end. Our inference methodology is able to capture this behavior by generating automata that count the number of periods of play. We conclude that our strategy inference technique enables us to better our understanding of the nature of strategic behavior in trust games.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 121.

in new window

Date of creation: 01 Mar 1999
Handle: RePEc:sce:scecf9:121
Contact details of provider: Postal:
CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA

Fax: +1-617-552-2308
Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:121. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.