No communication or interaction of
any kind outside that provided by the
system was permitted. The system
tabulated the total financial compensation earned by each subject throughout a session, and subjects were paid
by check at a later date following the
session. Compensation was strictly
limited to the actual earnings of each
individual subject according to their
own play and the rules of the particular
task or game; there was no compensation for mere participation. Following
a session, subjects were given an exit
survey in which they were asked to describe any strategies they employed
and behaviors they observed during
the experiments.
Within an individual experimen-
tal session, the overall collective task
or problem was fixed or varied only
slightly (for example, an entire session
on graph coloring), while the underly-
ing network structures mediating the
interaction would vary considerably.
Thus, the sessions were structured as
a series of short ( 1 to 5 minutes) ex-
periments, each with its own network
structure but on the same task. This is
the natural session format, since once
the task and incentives are explained
to the subjects, it is relatively easy for
them to engage in a series of experi-
ments on differing networks, whereas
explaining a new task is time-consum-
ing. Each experiment had a time limit
imposed by the system, in order to
ensure the subjects would not remain
stuck indefinitely on any single experi-
ment. In some sessions, there were
also conditions for early termination
of an experiment, typically when the
instance was “solved” (for example, a
proper coloring was found). A typical
session thus produced between 50 and
100 short experiments.
Summary of Experiments
The accompanying table briefly summarizes the nature of the experiments
conducted to date, describing the
collective task, the network structures used, the individual incentives
or mechanism employed, and some
of the main findings that we detail
below. Our first remark is on the diversity of these experiments along
multiple dimensions. In terms of the
Figure 1. Sample screenshot of subject Gui for a biased-voting experiment; many other
sessions involved similar Guis.
The central panel shows the subject’s
vertex (currently in the “blue” state)
with black edges to network neighbors
and their current states; red lines denote
edges between the subject’s neighbors.
The bottom action panel allows the subject
to change their current state any time,
while the top panel specifies their incentives
and elapsed time in the experiment.
Summary of experiments to date. ER stands for Erdös-Renyi, PA for preferential attachment.
task Description
graph coloring17
coloring and consensus10
networked trade13
networked bargaining3
independent set15
biased voting14
network formation16
networks
cycle+chords; PA
clique chain w/rewiring
eR; PA; structured;
all bipartite
assorted
assorted
eR and PA between types;
minority power
endogenous to the game
incentives/mechanism
differ with neighbors
differ/agree with neighbors
limit orders for trades
for opposing good
nash bargain on each edge
kings and pawns with
side payments
consensus with competing
individual preferences
biased voting minus edge
expenditures
Sample Findings
chords help; importance
of information view
opposite structure/task effects
comparison to equilibrium theory;
networked inequality aversion
behavioral price of obstinacy
side payments help;
conflict and fairness
well-connected
minority rules
poor collective
performance
oCTobeR 2012 | VoL. 55 | no. 10 | CommuniCAtionS oF thE ACm 59