Education Material on Evolutionary Game Theory & Experimental Economics
XYZW (201102)
CFH (201207,WP) Cycles and Instability in a RockPaperScissors Population Game: a Continuous Time Experiment (also) by Timothy N. Cason, Daniel Friedman, Ed Hopkins (Histroy, Program for the 2012 International ESA Conference, New York, Download June26th2012 version (also) Published version, 20130715, Reviews of Economics Studies, Comment CFH 2014 by Zhijian Wang, Siqian Zhu, BinXu @harvard.edu papers for students to presen (also)
HSNG (201202,WP) An experimental test of Nash equilibrium versus evolutionary stability (also) by Moshe Hoffman, Sigrid Suetens, Martin A. Nowak, Uri Gneezy
XW (201012, WP) Dynamical Pattern in a 2 x 2 Game with Human Subjects (Chinese) (also)
XW (201104, Pubilished in Book Page 13131326) Evolutionary Dynamical Pattern of 'Coyness and Philandering': Evidence from Experimental Economics
XYZW (201102, WP) Laboratory RPS Game Experimental Evaluations of the Evolutionary Dynamics TheoriesUCSC Econ 204B (2013 Spring) // Prof. Dan Friedman
Advanced Microeconomic Theory II
The second quarter of the Ph.D. microeconomics sequence
On
evolutionary game theory, look in the S&E library for books
by
William Sandholm (2010) and
Joergen Weibull (1997).
Draft chapters from Dan's book with Barry Sinervo
(due in 2014) can be
downloaded 2
the magic word isGameTheoryRPS.
A submitted paper is also attached below, reporting an experiment with rockpaperscissors.
Also, and older paper with KC Fung applying EvGames to an IO/Trade issue.
Population
Games and Evolutionary Dynamics
by William H. Sandholm. MIT Press, December 2010
Exploration dynamics in evolutionary games
PNAS 2009
Von Huyck
Figure 1a
graphs the vector field under the continuous time limit of the
two
population logit response dynamic with the noise parameter, , set
equal to 1. The axes measure
the frequency of action 1 in the first and
second population respectively. The points (1,0)
and (0,1) represent pure strategy equilibria in which everyone in one population
takes the action opposite
to the action taken by everyone in the second population. The
mixed equilibrium in the center of the
space is unstable, but vectors forcing
the populations away from the center are
small. (As the vector’s color goes
from black to red it represents smaller values.
The tail of the vector is also
proportional to size, but the head is not.) Note
also that the logit equilibria
with equal 1, denoted by red dots, are shifted slightly
towards the center of the
space. The shift will be more dramatic in the bargaining game
reviewed next. The grey shading represents
states in which all players have
a pecuniary incentive to conform to the emerging
convention.

1 
2 
3 
1 
3,3 
3,0 
6,4 
2 
0,3 
5,5 
0,0 
3 
4,6 
0,0 
0,0 
Figure 2a graphs the logistic response vector field for the game that results when action 2 becomes extinct in game DS, which will be denoted BOS. The black dots denote Nash equilibria and the red dots denote logistic equilibria (again with equal 1). The grey shaded regions indicate states in which everyone has a pecuniary incentive to conform to the emerging convention. Figure 2b graphs the results for five sessions run by hand and figure 2c graphs the results for three sessions run by computer. Again the points denote five period sums of action 1 for the row and column population. The sums can range from 0 to 35 (seven subjects choosing action 1 for five periods). Dots denote states in which the equal division action is extinct and circles denote states in which it is not. Numbers sequence the states by the time order they were observed.
Friendman 2009
Figure 4 shows an apparent pattern to the resolutions. It plots the Hawk fraction
only in the last 20 second time interval of each period. Except in Session 3, we
see that the separation trend builds over time, and that we approach an asymmetric
Nash equilibrium. The same data are replotted
in Figure 5,
using the conventions of Figure 1 and a trianglar smoother to help detect trends.
In sessions 2 and 4 we observe near convergence to a corner pure NE, while in session
1 we observe decisive movement only after period 16.
Optimization
incentives and coordination failure in laboratory stag hunt games
Battalio, L Samuelson Huyck  Econometrica, 2001
Human
strategy updating in evolutionary games
(pdf,
PNAS 2010) Evolutionary game dynamics describe not only frequencydependent genetic
evolution, but also cultural evolution in humans. In this context, successful strategies
spread by imitation. It has been shown that the details of strategy update rules
can have a crucial impact on evolutionary dynamics in theoretical models and, for
example, can significantly alter the level of cooperation in social dilemmas. What
kind of strategy update rules can describe imitation dynamics in humans? Here, we
present a way to measure such strategy update rules in a behavioral experiment.
Experimental Economics
Handbook(2008) C. Plott, V. Smith
Huyck2001 Data Replication Result
Mixed Strategy Nash Equilibrium