@hackage aivika3.0

A multi-paradigm simulation library

Aivika is a multi-paradigm simulation library with a strong emphasis on Discrete Event Simulation (DES) and System Dynamics (SD).

The library has the following features:

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

  • supports the event-driven paradigm of DES as a basic core for implementing other paradigms;

  • supports extensively the process-oriented paradigm of DES with an ability to resume, suspend and cancel the discontinuous processes;

  • allows working with the resources based on specified queue strategies (FCFS/FIFO, LCFS/LIFO, SIRO, static priorities and so on);

  • allows customizing the infinite and finite queues based on strategies too;

  • allows defining a queue network based on infinite streams of data and their processors, where we can define a complex enough behaviour just in a few lines of code;

  • allows simulating circuits with recursive links and delays;

  • supports the activity-oriented paradigm of DES;

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

  • allows creating combined discrete-continuous models as all parts of the library are well integrated and this is reflected directly in the type system;

  • the arrays of simulation variables are inherently supported;

  • supports the Monte-Carlo simulation;

  • the simulation model can depend on external parameters;

  • uses extensively signals for notification;

  • allows gathering statistics in time points;

  • hides technical details in high-level simulation computations (monads and arrows).

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.

The PDF documentation is available on the Aivika Wiki [3] website.

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

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

[3] https://github.com/dsorokin/aivika/wiki

P.S. Aivika is actually a genuine female Mari name which is pronounced with stress on the last syllable.