PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Parallel and Distributed Agent-based Simulation of large-scale socio-technical Systems with loosely coupled Virtual Machines

Challenges and Pitfalls

PD Dr. Stefan Bosse

sbosse@uni-bremen.de

University of Bremen, Dept. Mathematics and Computer Science, Bremen, Germany

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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Introduction

Agent-based systems are inherently distributed and parallel by a distributed memory model!

Agents are loosely coupled - a precondition for parallelisation

But agent-based simulation is often characterised by a shared memory model and tight coupling of agents!

This work investigates architectures and methods for parallel and distributed large-scale agent-based simulations

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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Simulation of Socio-Technical Systems

Simulation of large-scale socio-technical systems (like in the Smart City context) is a challenge due to high number of entities and complex dynamic interaction networks

  • Simulation can map physical (materialised) entities on state-based agents like:
    • Humans
    • Vehicles
    • Machines
    • Buildings
    • Traffic signals
    • Robots
    • ...
  • NetLogo is a widely used agent-based simulator (some of its operational semantics is addressed in this work)
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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Agent Model and Agent-based Methods

Agent
Loosely coupled software unit or a hardware device (robot) situated in a specific environment posing perception, interaction, knowledge representation, learning, and self-* capabilities.
Agent-based Computing
Agent architecture representing a software and communication model (mobile software processes).
Agent-based Simulation
Bottom-up approach for simulation and computation of dynamic large-scale systems and world. Agents are elementary cells connecting to an emergent system (holonic design principle).
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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Agent Model and Agent-based Methods

The agent behaviour consists of:

  1. Computation (only modifying internal agent state);

  2. Communication (with other agents and the environment);

  3. Actions (modifying the state of other agents or the environment).

  • The most important parts addressed in this work are communication and interaction of agents.

  • Computation is always decoupled from other processing units and can be parallelised without any limiting constraints.

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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Agent Classes

There are two main agent classes:

Computational Agents
A computational agent represents a (mobile) software process with the primary goal of computation, typical situated and processed in real world.
Physical Agents
A physical agent represents a physical entity (machine, human, animal, device, avatar), typically situated and processed only in simulation and virtual worlds. Example: NetLogo agents
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PD Stefan Bosse - Parallel and Distributed Agent-based Simulation

Agent Classes