@hackage aivika0.7

Aivika is a multi-paradigm simulation library which has the following features:

• allows defining recursive stochastic differential equations of System Dynamics (unordered as in maths via the recursive do-notation);

• has a basic support of the event-driven paradigm of the Discrete Event Simulation (DES);

• has a basic support of the process-oriented paradigm of DES with an ability to resume, suspend and cancel the discontinuous processes;

• allows working with limited resources (you can define your own behaviour or use the predefined queue strategies);

• allows customizing the queues (you can define your own behaviour or use the predefined queue strategies);

• supports the activity-oriented paradigm of DES;

• supports the basic constructs for the agent-based modeling;

• allows creating combined discrete-continuous models;

• the arrays of simulation variables are inherently supported (this is mostly a feature of Haskell itself);

• supports the Monte-Carlo simulation;

• the simulation model can depend on external parameters;

• uses extensively the signals to notify the model about changing the reference and variable values;

• allows gathering statistics in time points;

• hides the technical details in high-level simulation monads (three of them support the recursive do-notation).

Aivika itself is a light-weight engine with minimal dependencies. However, it has additional packages Aivika Experiment [1] and Aivika Experiment Chart [2] that offer the following features:

• automating the simulation experiments;

• saving the results in CSV files;

• plotting the deviation chart by rule 3-sigma, histogram, time series, XY chart;

• collecting the summary of statistical data;

• parallel execution of the Monte-Carlo simulation;

• have an extensible architecture.

All three libraries were tested on Linux, Windows and OS X.

Please read the PDF document An Introduction to Aivika Simulation Library [3] for more details (a little outdated). This document is included in the distributive of Aivika but you can usually find a more recent version by the link provided.

[1] http://hackage.haskell.org/package/aivika-experiment

[2] http://hackage.haskell.org/package/aivika-experiment-chart

[3] https://github.com/dsorokin/aivika/blob/master/doc/aivika.pdf