gamar: an r interface to the gama agent-based simulation ...gamar: an r interface to the gama...

gamar: an R interface to the GAMA agent-based simulation platform

Marc ChoisyLucie ContaminHo Bich HaiNicolas MarilleauJean-Daniel Zucker

population-based individual-based agent-baseddifferential equations Gillespie algorithms

Increased level of detail

deSolve

adaptivetauGillespieSSAdde

diffeqrPBSddesolve

bvpSolve

Agents are• autonomous • heterogeneous • active • adaptive

Population dynamics modeling

population-based individual-based agent-baseddifferential equations Gillespie algorithms

Increased level of detail

deSolve

adaptivetauGillespieSSAdde

diffeqrPBSddesolve

bvpSolve

Agents are• autonomous • heterogeneous • active • adaptive

Population dynamics modeling

RNetLogorrepastNetLogoR

NetLogo

Performance

Ease of use

GAMA

repast.github.io ccl.northwestern.edu/netlogo gama-platform.github.io

since 2007since 1999 since 2000

Agent-based modeling platforms

RNetLogorrepastNetLogoR

NetLogo

Performance

Ease of use

GAMA

repast.github.io ccl.northwestern.edu/netlogo gama-platform.github.io

since 2007since 1999 since 2000

Agent-based modeling platforms

• a language: GAML

• a user-interface

• a fast and parallelized engine

• integration with GIS data

https://gama-platform.github.io

The GAMA simulation platform

• a language: GAML

• a user-interface

• a fast and parallelized engine

• integration with GIS data

https://gama-platform.github.io

The GAMA simulation platform

.gaml

model

outputs

1. design model

2. load

model

3. design experiment plans

5. analyse simulations

4. run experiment

experiment object

The gamar R package

run_experiment()load_experiment()

fullfact(), repl()

makemovie()

.gaml

model

outputs

1. design model

2. load

model

3. design experiment plans

5. analyse simulations

4. run experiment

experiment object

The gamar R package

run_experiment()load_experiment()

fullfact(), repl()

makemovie()

.gaml

model

outputs

1. design model

2. load

model

3. design experiment plans

5. analyse simulations

4. run experiment

experiment object

The gamar R package

run_experiment()load_experiment()

fullfact(), repl()

makemovie()

several columns for parameters values - always first columns - names start with p_

several columns for monitored variables - just after the parameters columns - names start with r_

one column for simulations durations - always penultimate position - named tmax

one column for seeds values - always penultimate position - named seed

The experiment class

one list-column for simulations outputs - always last position - named output

/Users/gamar/models/sir/sir.gaml/Users/gamar/models/sir/output

outputNANANANANANA...

NANANANANANA

output<data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]>

.

.

.<data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]><data.frame[1000,3]>

several columns for parameters values - always first columns - names start with p_

several columns for monitored variables - just after the parameters columns - names start with r_

one column for simulations durations - always penultimate position - named tmax

one column for seeds values - always penultimate position - named seed

The experiment class

one list-column for simulations outputs - always last position - named output

/Users/gamar/models/sir/sir.gaml/Users/gamar/models/sir/output

Visualizing simulation resultswith(sir$output[[1]], plot(Step, r_I, ylab = "nb. infected")

path_to_movie <- make_movie(pp$output[[1]], "r_main_display")

https://r-and-gama.github.io/gamar

https://r-and-gama.github.io/gamar