@hackage aivika4.3.5

A multi-method simulation library

Aivika is a multi-method simulation library focused on discrete event simulation (DES) with partial support of system dynamics and agent-based modeling.

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;

  • supports the resource preemption;

  • allows defining a queue network based on streams of data (transacts) and their processors;

  • allows simulating circuits with recursive links and delays;

  • supports the activity-oriented paradigm of DES;

  • supports basic constructs for the agent-based modeling such as agents, states, timeout and timer handlers;

  • 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, streams and arrows).

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

  • automating 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;

  • has an extensible architecture.

The charting package has two interchangeable back-ends [3, 4], where one of them uses Cairo and it is more preferable.

The PDF documentation and installation instructions are available on the Aivika Wiki website [5].

Moreover, the method was generalized [6] and applied to nested simulation [7] and parallel distributed simulation [8].

The libraries were tested on Linux, Windows and OS X.

A more full information about Aivika is available on the project website [9].

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

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

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

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

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

[6] http://hackage.haskell.org/package/aivika-transformers

[7] http://hackage.haskell.org/package/aivika-branches

[8] http://hackage.haskell.org/package/aivika-distributed

[9] http://www.aivikasoft.com/en/products/aivika.html

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