# Probabilistic Relational Agent-based Models

## TL;DR

PRAM introduces a probabilistic framework for agent-based models, enabling integration with probabilistic models, supporting dynamic simulation, and offering potential efficiency improvements over traditional agent-based simulation methods.

## Contribution

It extends probabilistic relational models and lifted inference to dynamic agent-based modeling, providing a sound probabilistic foundation and efficiency benefits.

## Key findings

- Enables integration of agent-based and probabilistic models.
- Supports dynamic simulation within a probabilistic framework.
- Potentially more efficient than traditional agent-based simulation.

## Abstract

PRAM puts agent-based models on a sound probabilistic footing as a basis for integrating agent-based and probabilistic models. It extends the themes of probabilistic relational models and lifted inference to incorporate dynamical models and simulation. It can also be much more efficient than agent-based simulation.