Can genetic algorithms explain experimental anomalies? An application to common property resources

Human    Nash

Artificial agents,
_______pm=0.02, pc=0.00________

Artificial agents,
______T=64_______

agents

H     Equilibriu ’

T=32

(3)

T=64    T=400

pm=0.02 pm=0.01

(1)       m (2)

(4)          (5)

pc=0.40   pc=0.00

(6)          (7)

GROUP RESULTS

X - Resource use

0.95 confidence interval on X

131.32     128.00

[127.25,           -

135.39]

131.02
[130.96,
131.08]

130.40    130.02

[130.35,    [129.98,

130.45]    130.06]

130.52       129.82

σ(X) -Standard deviation of use over time

12.95       0.00

17.50

15.03      14.04

14.53       9.51

Efficiency

28.4%    39.5%

26.85%

29.75%   31.16%

29.75%   33.55%

Periods with negative earnings

15.5%    0.00%

19.59%

16.00%   14.97%

16.12%    8.22%

INDIVIDUAL RESULTS

MAX2 -Agent with maximum use (2)

37.92      16.00

28.71

27.72     27.01

25.04     25.89

MIN2 - Agent with minimum use (3)

9.57      16.00

5.93

8.75      11.35

9.31        9.81

D2 - Individual difference, (2)-(3)

SD2 -Individual use standard deviation
0.95 confidence interval of SD2

Test of H0 {XH=XGA}

Test of H0 {SD2H=SD2GA}

28.35       0.00

9.05       0.00

[5.13,             -

33.42]

22.78      18.97      15.66

5.76       4.79       4.09

[5.04, 6.65] [4.19, 5.53] [3.58, 4.72]

Cannot Cannot Cannot
reject H0 reject H0 reject H0

Cannot   p-value= H0 rejected

reject H₀     0.05________________

15.73      16.08

Notes to Table 1: T=total periods of simulation; 32 periods considered in

the statistics, T-32,...,T. If T=32 all

the periods of the simulation are included in the

statistics. The basic action is the use level of the resource, xitk, by agent i

Q

=1,..,8 at period t=1,..,T for run k=1
T

,..,100 (random seeds 0.005 through 0.995). The

aggregate resource use Xtk= ∑ x_itk and its average
i=1

for each run is Xk =

¹ ∑Xtk
τt=T-τ+1

. The significance tests are carried out, using X_k as a single observation,