PyPRAM

Probabilistic Relational Agent-based Models (PRAMs) is a modeling and simulation framework that puts agent-based models (ABMs) on a sound probabilistic foundation. When compared to equivalent ABMs, PRAMs are:

• More space- and time-efficient (due to agent population encoding)

• More sound (due to probabilistic foundation)

• More expressive (due to allowing relations)

Contents:

• Introduction
  • Dependencies
  • Installation
  • Basic API Usage
• Details
  • Modeling Levels
  • Ordinary Differential Equations
  • Composite Simulations
  • Mass Dynamics
  • Trajectories and Trajectory Ensembles
• Example Simulations
  • Flu at Allegheny County Schools
• Front-Ends
  • Automatic Agent Population Generation
  • PRAMity
  • Venture Capital App
• API Reference
  • Subpackages
  • Submodules
  • pram.data module
  • pram.entity module
  • pram.graph module
  • pram.pop module
  • pram.rule module
  • pram.signal module
  • pram.sim module
  • pram.traj module
  • pram.util module
  • Module contents
• License

Indices and tables

• Index

• Module Index

• Search Page