an annotated list of links
by Craig Reynolds
Individual-based models are simulations based on the global
consequences of local interactions of members of a population. These
individuals might represent plants and animals in ecosystems,
vehicles in traffic, people in crowds, or autonomous characters in animation
and games. These models typically consist of an environment or
framework in which the interactions occur and some number of individuals
defined in terms of their behaviors (procedural rules) and
characteristic parameters. In an individual-based model, the
characteristics of each individual are tracked through time. This stands in
contrast to modeling techniques where the characteristics of the population
are averaged together and the model attempts to simulate changes in these
averaged characteristics for the whole population. Individual-based models
are also known as entity or agent based models, and as
Some individual-based models are also spatially explicit meaning that
the individuals are associated with a location in geometrical space. Some
spatially explicit individual-based models also exhibit mobility,
where the individuals can move around their environment. This would be a
natural model, for example, of an animal in an ecological simulation.
Whereas plants in the same simulation would not be mobile. Some
individual-based models are not spatially explicit, for example a simulation
of a computer network might be based on individual models of the networked
computers, but their location would be irrelevant. Spatially explicit
models may use either continuous (real valued) or discrete
(integer valued, grid-like) space.
Individual-based models are a subset of multi-agent systems which
includes any computational system whose design is fundamentally composed of
a collection of interacting parts. For example an "expert system" might be
composed of many distinct bits of advice which interact to produce a
solution. Individual-based models are distinguished by the fact that each
"agent" corresponds to autonomous individual in the simulated domain.
There is an overlap between individual-based models and
Certainly cellular automata are similar to spatially-explicit, grid-based,
immobile individual-based models. However CAs are always homogeneous and
dense (all cells are identical), whereas a grid-based individual-based
model might occupy only a few grid cells, and more than one distinct type
of individual might live on the same grid. (Of course a CA can have cells
in various states, and so represent concepts like empty or
occupied by type 3. Perhaps the significant difference is whether
the simulation's inner loop proceeds cell by cell, or individual by
individual. (Although that distinction is muddied by parallel-processing
hardware.)) The philosophical issue is whether the simulation is based on a
dense and uniform dissection of the space (as in a CA), or based on
specific individuals distributed within the space.
Of course, note that everyone uses terminology differently, so take the
definitions above with a grain of salt. ("Your mileage may differ.")
My interest in this area began when I made a model of
bird flocks and related group motion. As a result I am particularly
interested in individual-based models using spatially explicit mobile agents
in continuous space. This bias may be reflected in the selection of
resources listed below.
These are general purpose software toolkits useful for implementing
Listed below are applications of individual-based models, arranged by general
- Ecology and Biology:
- Mixed ecosystems
- Marine Invertebrates
- Non-species-specific models, and other topics
Tragedy of the Commons Java applets and commentary by Walter
Korman (from the now defunct weekly column
Based on Garrett Hardin's 1968 paper.
- Parallel Software
Tools for Ecological Simulation including the Java-based
GUST which runs an interactive version of their Szymanski-Caraco
cellular automata model. See their
Guide to Related Research.
- Ecomachines and
Spatial Modeling in Ecology and Biology was a workshop held January
13-16, 1996 at the Santa Fe Institute.
- Gecko, a
spatial individual-based simulator for modeling ecosystem dynamics, by
ECOTOOLS uses individual-based models to study animal behavior
and ecological issues. See descriptions of various
ECOSIM reimplemented models: schooling, flocking, storks,
dragonflies, crowns, largemouth bass, northern cod.
- Theoretical Ecology of Spatial Heterogeneity: An IBM Approach
ongoing work by Kim
Cuddington on "...the effects of limited mobility and spatial
structure or heterogeneity on the population dynamics and stability of
communities." See also these resources on
- Methods, Conceptions &
Ideas on Ecological Modelling by
Andrey Tsyplianovsky. This extensive site covers many aspects of
ecological modeling and includes a comprehensive list of links on
Ten years of individual-based modelling in ecology: what have we learned,
and what could we learn in the future? (1999) by
in a special issue of Ecological Modelling on
- Forager, from
Amber Waves Software, simulates
foraging (feeding behavior). Users can set up animal behavior models,
graphically design the foraging environment and specify behavior rules.
- Papers from the
Third International Conference/Workshop on Integrating GIS and
Environmental Modeling January 21-25, 1996, Santa Fe, New Mexico:
From Individuals to Populations, papers from a 1998 International
Workshop and Young Scientists School held in Ceske Budejovice, Czech
- Instructional Tools:
- Modeling Humans (and Artificial Societies)
- Human Crowds: motion and psychology
- An Agent
Based Simulation Environment for Public Order Management Training by
is a tool to help train training police officers to manage large public
gatherings (crowds, demonstrations, marches). See also the page for the
CACTUS (Command And Control Training and Planning Using Knowledge
Based Simulation) system.
G. Keith Still
is used to simulate the motion of large crowds of people. It can
handle crowds of more than 100,000 people.
- Animation Science Corporation sells
tools to model the motion of large crowds with their
software, based on an efficient engine for
interacting particle systems.
Neural Simulation Toolkit), an artificial-life laboratory for exploring
self-organized emergent behavior in land combat, by
Andy Ilachinski of the (US)
Center For Naval Analyses.
The Collective Action Project by
and John McCarthy, studies
individual and collective actions of people in large temporary
gatherings (crowds, mobs, demonstrations). See also
A Computer Simulation of a Sociological Experiment (1995) by
based on the GATHERING simulation written by William T. Powers, based
on Perception Control Theory.
Agent-Based Model of Seating In A Theater a Java-based class project
by Yale Wang. See also his version of
Schelling's Segregation Model and the
problem: how the appropriate number of people decide to show up for
Modeling Audience Group Behavior by
Nuria Oliver and
describes an agent based model (spatially explicit, discrete space,
non-mobile) of synchronization and other decentralized collaborative
behaviors of a group audience.
- Artificial Societies
- Interpersonal Communication
- other topics
- Playing the
game of life by Rita Koselka (an April 7, 1997 article from
Forbes) covers individual-based
models of the music CD business by the Emergent Solutions Group of
the stock market by
Arthur and John Holland, the
Sugarscape model by
Joshua Epstein and Robert Axtell, and Challenge from
Aspen, a microanalytic model to simulate the U.S. economy. Aspen
uses economic agents to represent the various decision-making segments,
and the microanalytic simulation process models each agent individually.
See also this earlier
Computational Economics (ACE) by
Leigh Tesfatsion, a
computational study of economies modeled as evolving decentralized
systems of autonomous interacting agents. Which seeks to explain these
global regularities in economic processes from the bottom up. See also
How Economists Can Get Alife: Abbreviated Version
Agent based simulation of artificial electricity markets by
Raimo P. Hämäläinen et al. models how customers
respond to different price patterns for electrical power.
Artificial Life Simulation of the Textile/Apparel Marketplace: An
Innovative Approach to Strategizing about Evolving Markets by
Evelyn L. Brannon,
Lenda Jo Anderson, R. Alan Donaldson, Thomas E. Marshall,
Pamela V. Ulrich.
Modeling of Global Innovation Diffusion, Diploma Thesis of
and Friedemann Buergel (aka
Bürgel) uses an agent based simulation model called LEM 1.1 to
visualize cultural, institutional, economic and legal key factors of
spacio-temporal diffusion of new technologies (specifically Light
Electric Vehicles (LEVs)).
Agent Based Simulation of the Hotelling Game by Michael Friedlander
and David Sumpter a
spatial variation on a model of the pricing of identical goods by the
only two shops in a town.
Market Organisation by
Gerard Weisbuch ,
Alan Kirman and
Dorothea Herreiner, also available as
SFI working paper 95-11-102.
- Traffic and vehicle simulations
- Hank is an interactive
automotive driving simulation with an individual-based model of
autonomous vehicle traffic and pedestrians. These provide the dynamic
environment and allow
authoring scenarios. By
Joe Kearney and the
- MITSIM A
Microscopic Traffic Simulator for Evaluation of Dynamic Traffic
Management Systems developed at MIT's
Intelligent Transportation Systems
lab by Qi Yang and
Haris N. Koutsopoulos
Microsimulation of road traffic a very nice Java applet demonstrating
a continuous "microscopic" model of traffic dynamics in several scenarios
Dirk Helbing. See also
Discrete Force Model for Pedestrian Motion Java applets by
Kai Bolay and
Stop-and-Go Science (1999) by
Peter Weiss in
Science News Online.
Survey article: "by better understanding traffic flow, researchers hope
to keep down highway congestion."
Transportation Analysis and Simulation System at the
Los Alamos National Laboratory.
"TRANSIMS models a metropolitan region with a representation of the
inhabitants, their activities, and the transportation infrastructure.
TRANSIMS then simulates the movement of individuals across the
transportation network, including their use of vehicles such as cars or
buses, on a second-by-second basis."
- Smartest Project
(Simulation Modelling Applied to Road Transport European Scheme Tests) by
See also these lists of traffic micro-simulation
- The STEER Traffic
Simulator (Signals/Traffic Emulator with Event-based Responsiveness)
is a program intended to simulate traffic on an urban network, modeling
up to tens of thousands of vehicles.
- METROPOLIS 1.0 is a
modular system for Dynamic Traffic Simulations: It is aimed towards
on-line as well as off-line simulations of traffic flows in an urban
context and for large networks.
SmartPath simulation and animation package for traffic studies.
See also Smart AHS
a specification, simulation and evaluation framework for modeling,
control and evaluation of Automated Highway Systems (AHS). Both part of
(Partners for Advances Transit and Highways)
- Demonstration of
Traf-Netsim for Traffice Operations Management: Final Report (1991)
by Joan D. Sulzberg and
J. Demetsky. A "microscopic level" simulation of cars, buses and
Demos an individual-based simlulation model of a set of elevators in
a ten story building. Uses a Java applet graphical front-end and a
MODSIM III back-end
running on a remote server.
- Animation and Interactive Multimedia
- Related topics
Laboratories and Groups
Economic Simulation Conference Conference Proceedings February 9-10,
From Animals To Animats (SAB98) Fifth International Conference
of the Society for Adaptive Behavior, University of Zurich, August
17-21 1998, Zurich, Switzerland.
- Sixth International Conference on
Artificial Life (Alife VI) June 27-29, 1998, University of
California, Los Angeles, USA.
Multi-Agent Systems and Agent-Based Simulation (MABS 98)
one of the eight meetings (including
Conference on Multi-Agent Systems (ICMAS 98)) comprising
- First International Conference
on Virtual Worlds, July 1-3, 1998, International Institute of
Multimedia, Paris, France.
Interaction and Global Phenomena in Vegetation and Other Systems,
April 19-23, 1999,
Institute for Mathematics and its Applications,
University of Minnesota
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Last update: Ocotber 22, 1999