Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Introduction to Multi-Agent Simulation for Analysts and Decision Makers
 

Summary: 1
Introduction to Multi-Agent Simulation
for Analysts and Decision Makers
Peer-Olaf Siebers and Uwe Aickelin
University of Nottingham, UK
Introduction
When designing systems that are complex, dynamic and stochastic in nature,
simulation is generally recognised as one of the best design support technologies, and
a valuable aid in the strategic and tactical decision making process. A simulation
model consists of a set of rules that define how a system changes over time, given its
current state. Unlike analytical models, a simulation model is not solved but is run and
the changes of system states can be observed at any point in time. This provides an
insight into system dynamics rather than just predicting the output of a system based
on specific inputs. Simulation is not a decision making tool but a decision support
tool, allowing better informed decisions to be made. Due to the complexity of the real
world, a simulation model can only be an approximation of the target system. The
essence of the art of simulation modelling is abstraction and simplification. Only
those characteristics that are important for the study and analysis of the target system
should be included in the simulation model.
The purpose of simulation is either to better understand the operation of a

  

Source: Aickelin, Uwe - School of Computer Science, University of Nottingham

 

Collections: Computer Technologies and Information Sciences