## PDToolbox
PDToolbox is a matlab implementation of some evolutionary dynamics from game theory. The current version supports the implementation of replicator dynamics, Maynard Smith's replicator dynamics, Smith dynamics, logit dynamics, and Brown-von Neumann-Nash dynamics. Also, it can be used to run revision protocols, that is, population games with small number of agents per population.
This toolbox is designed to facilitate the implementation of any game, regardless of the number of populations, strategies per population, and fitness function. It has some pre-build methods to implement different dynamics, revision protocols, and to plot the evolution of the state of each population. This software is distributed under BSD license.
## Installation
1. Download files from the 'git' repository with the following command:
git clone https://github.com/carlobar/PDToolbox_matlab
Or download and extract the files directly from the following link:
https://github.com/carlobar/PDToolbox_matlab/archive/master.zip
2. Open matlab and add the path of the following directories:
path(path, '[download directory]/PDToolbox_matlab')
path(path, '[download directory]/PDToolbox_matlab/dynamics')
path(path, '[download directory]/PDToolbox_matlab/graphs')
path(path, '[download directory]/PDToolbox_matlab/test')
The path can be verified with the command 'path'.
The path can be added automatically by running 'add_path.m'.
## Running the toolbox
In order to use the toolbox we must define the parameters of the game in a data structure. Some parameters that must be defined are:
* Number of populations,
* Strategies of each population
* Evolutionary dynamics
* ODE solver
* Fitness function
The following examples are included in the 'test' directory:
'test1.m': game with one population and three strategies per population.
'test2.m': game with two populations and two strategies per population.
'test3.m': game with one population, three strategies per population, and combined dynamics.
'test_finite_population1.m': a game with small number of agents per population.
'test_maximization.m': application to a maximization problem using one population.
'test_maximization_b.m': application to a maximization problem using multiple populations.
'electricity grid/test_electricity_system.m': application to demand response programs.
## Documentation
An introduction to evolutionary dynamics with some examples is available at:
https://github.com/carlobar/PDToolbox_matlab/blob/master/docs/documentation.pdf
## License
PDToolbox is released under the [BSD License](http://opensource.org/licenses/BSD-3-Clause)
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PDToolbox_matlab-master.zip
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PDToolbox_matlab-master.zip (100个子文件)
documentation.bbl 2KB
references.bib 34KB
documentation.dvi 76KB
test1_simplex_rd.eps 518KB
test1_simplex_smith.eps 401KB
test_combined.eps 400KB
test1_simplex_logit.eps 397KB
test2_simplex_rd.eps 359KB
test2_ev_rd.eps 346KB
test1_simplex_bnn.eps 336KB
test1_ev_rd.eps 326KB
test2_ev_smith.eps 321KB
test2_ev_maynard_rd.eps 321KB
test2_ev_logit.eps 320KB
test_finite_logit_choice_ev.eps 318KB
test2_ev_bnn.eps 317KB
test_finite_proportional_imitation_ev.eps 311KB
test1_ev_smith.eps 307KB
test_combined_ev.eps 307KB
test2_simplex_maynard_rd.eps 306KB
test1_ev_logit.eps 305KB
test_finite_pairwise_comparison_ev.eps 305KB
evolution_u.eps 304KB
test_finite_comparison2average_ev.eps 303KB
test1_ev_bnn.eps 302KB
test_finite_logit_choice.eps 298KB
evolution_i.eps 290KB
test2_simplex_smith.eps 283KB
accumulated_i.eps 280KB
maximization_b.eps 278KB
maximization_a.eps 277KB
test2_simplex_logit.eps 277KB
test_finite_proportional_imitation.eps 275KB
running_time_pop.eps 262KB
running_time_str.eps 262KB
running_time_smith_pop.eps 261KB
running_time_smith_str.eps 261KB
test2_simplex_bnn.eps 259KB
test_finite_pairwise_comparison.eps 254KB
test_finite_comparison2average.eps 250KB
final_state.eps 242KB
LICENSE 1KB
definition.m 5KB
graph_ev_dynamics.m 4KB
graph_incentives_evolution.m 4KB
test_electricity_system_test_boundary.m 3KB
test_electricity_system.m 2KB
run_game_finite_population.m 2KB
graph_fitness.m 2KB
smith_b.m 2KB
incentives_comb.m 2KB
run_game.m 2KB
bnn.m 2KB
logit.m 2KB
smith.m 2KB
maynard_rd.m 2KB
rd.m 1KB
graph_evolution.m 1KB
logit_choice.m 1KB
proportional_imitation.m 1KB
pairwise_comparison.m 1KB
comparison2average.m 1KB
test2.m 1KB
test_finite_population1.m 1KB
combined_dynamics.m 1KB
test1.m 1KB
test3.m 1KB
stopevent.m 966B
test_maximization_b.m 958B
test_maximization.m 953B
graph_simplex.m 929B
graph_multi_pop.m 854B
strategy.m 843B
state.m 636B
utility_incentives.m 582B
utility.m 575B
add_path.m 440B
fitness_user_inefficient.m 312B
fitness_user.m 302B
graph_final_state.m 242B
fitness1.m 229B
fitness3.m 219B
fitness2.m 210B
p_x.m 87B
v_x.m 85B
h_i.m 53B
Makefile 370B
README.md 3KB
test1.m.orig 2KB
documentation.pdf 1.08MB
documentation.ps 9.63MB
cut.sh 256B
example_dr.tex 11KB
documentation.tex 9KB
implementation.tex 9KB
evolutionary_dynamics.tex 8KB
maximization.tex 5KB
introduction.tex 4KB
multipopulation.tex 4KB
combined_dynamics.tex 2KB
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