Experimental data: Inferring strategies from observations in long iterated prisoner’s dilemma experiments

While many theoretical studies have revealed the strategies that could
lead to and maintain cooperation in the Iterated Prisoner's Dilemma,
less is known about what human participants actually do in this game and
how strategies change when being confronted with anonymous partners in
each round. Previous attempts used short experiments, made different
assumptions of possible strategies, and led to very different conclusions.
We present here two long treatments that differ in the partner matching
strategy used, i.e. fixed or shuffled partners. Here we use unsupervised
methods to cluster the players based on their actions and then Hidden
Markov Model to infer what are those strategies in each cluster. Analysis
of the inferred strategies reveals that fixed partner interaction leads to
a behavioral self-organization. Shuffled partners generate subgroups of
strategies that remain entangled, apparently blocking the self-selection
process that leads to fully cooperating participants in the fixed partner
treatment. Analyzing the latter in more detail shows that AllC, AllD, TFT-
and WSLS-like behavior can be observed. This study also reveals that long
treatments are needed as experiments less than 25 rounds capture mostly
the learning phase participants go through in these kinds of experiments.