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Analysis of Self-Organizing Decision-Making Systems

(last update: 2013/05/03)

Supplementary material for:
Heiko Hamann
A Reductionist Approach to Hypothesis-Catching for the Analysis of Self-Organizing Decision-Making Systems

This is some very simple and not documented code that implements two simulations and the analysis discussed in the above paper.

A) BEECLUST

files: beeclust_sim.c beeclust_analysis.c

requirements: zlib (on an Ubuntu system: sudo apt-get install zlib1g-dev)

How to compile and run:
    gcc -Wall beeclust_sim.c -lm -lz -O3 -o beeclust_sim
    ./beeclust_sim
    gcc -Wall beeclust_analysis.c -lm -lz -O3 -o beeclust_analysis
    ./beeclust_analysis

How to plot the results using gnuplot:
example for transition HS_l -> HS_lM_r (see paper):
   plot "transitionRatios" u ($2)/25:($10)/($10+$9) w l
example for transition M_l -> M_r:
   plot "transitionRatios" u ($2)/25:($4)/($4+$6) w l

B) Alignment in locusts

file: locust2in1.cpp
requirements: boost C++ libraries (on an Ubuntu system: sudo apt-get install libboost-all-dev)

How to compile and run:
    g++ -Wall locust2in1.cpp -lm -O3 -o locusts
    ./locusts

How to plot the results using gnuplot:
example for transition LL -> RL (see paper):
    plot "transitionRatios" u ($2/45):($3/($3+$10)) w l

next steps: increase number of samples (code line: "#define SAMPLES ..."), test different Markov chains etc.