What is Agent-Based What is Agent-Based Modeling?Modeling?

Virginia A. Folcik Nivar Ph.D.Virginia A. Folcik Nivar Ph.D.

“Essentially, all models are wrong, but some are useful.”

George Box, Statistician and Prof. Emeritus, Univ. of Wisconsin-Madison,Industrial and Systems Engineering

“Remember that all models are wrong; the practicalquestion is how wrong do they have to be not to be useful.”

ModelModel VS.VS. SimulationSimulation

MODEL SIMULATION

•less detail •generalizable•involves learning process •an art form•answers “what if” questions

•more detail •not generalizable to all situations•answers specific questions

Sub-atomic particlesAtoms

Molecules Macromolecules (DNA, RNA, Proteins)

Organelles Cells (Organisms)

TissuesOrgans

Organ systems (Immune System)Organisms

Populations [Societies, Economies, Ecologies (90%), Businesses]

What can be modeled?

SYSTEMS BIOLOGY{

ALL CAN BE STUDIEDWITHMATHEMATICALORAGENT-BASED MODELING

“Swarm Intelligence”•Social insects are extremely successful creatures•They maintain their existence following simple rules based on local information•They self-organize, have no central control•They exhibit flexibility (adjust task allocation)•Colonies are robust•They use indirect communicationEx. Southwest Airlines Cargo Operations

Bonabeau, Dorigo and Theraulaz, 1999

Complex Adaptive Systems

•Large collections of autonomous members•Members react to their local environment according to a set of internal rules•No centralized control•Exhibit emergent behavior•Exhibit stigmergy Examples: insect colonies, societies, ecologies, economies, biologies, business firms, cities, schools of fish, flocking birds, driversin traffic, terrorist networks…

Emergence

Complex systems arise from the simple behavior of the individuals that constitute them.

The whole is greater than the sum of the parts.

Examples of emergent phenomena:•Braess’s Paradox (1968) Adding more lanes to a highway often makes traffic jams worse. •Employee bonuses result in reduced productivity.•An increase in the number of shoppers in a supermarket decreases sales of certain products.•A deficiency in innate immunity (dendritic cells) results in the increased incidence of hypersensitivity reactions.

Stigmergy

The indirect communications that take place between individuals in a complex system.

(French entomologist Pierre-Paul Grassé in 1950’s)

•Cytokines and chemokines•PheromonesEx. France Telecom, British Telecom, and MCI Worldcom,phone call routing.

Agent-Based ModelingAgent-Based Modelinga.k.a. Individual-Based Modeling, Bottom-Upa.k.a. Individual-Based Modeling, Bottom-Up

Modeling or Pattern-Oriented ModelingModeling or Pattern-Oriented Modeling

AgentAgent

EnvironmentEnvironment

Perceptions

Actions

Rules

State Diagrams

A B C

StartState

Final State

In the immune simulation, contact with cells or signals(or their absence) trigger the transitions from one state to the next.

Activated

Zone 2

State 0

State 1

Activated T1*

Inactive T0Ag-m

atched DC1 State 3No MK1 or CK1

Memory T1*

DC1

CK1

State 2

CK2

State 4

Memory T2*

DC2

State Diagram: T cells

progeny to Zone 2

2 T1**

2 T2**

Activated T2*

Initialization

DURATION_CK1_Zone 2

DURATION_CK2_Zone 2

NumT1_ToSend

NumT2_ToSend

All T

cells movin

g in Z

one 2

*Moves randomly seeking an Ag-matched B1 or B2. Contact with B adds time to life.

**First Ag- and type-matched DCcontact with a T-cell causes prolifer-ation of T’s into Zone 2.†DC contact extends life.‡Time is up, apoptosis.

State 9

No MK1 or CK1

Ag-matched DC2 ‡

‡

Apoptosis

1 T1

1 T2 †

††

†

Agent-Based Modeling:Agent-Based Modeling:Currently the best tool for studying Currently the best tool for studying behaviorbehavior within a complex system within a complex system

•ABM’s capture emergent phenomena.

•Provide a natural (logical) description of a complex system. Experts in a field can relate to the model.

•Agent-based modeling is flexible.

•Explain phenomena by “growing” them.

•Abstraction: the process of removing detail from a representation.

Choosing the appropriate level of abstraction

Grimm et al. (2005) Science 310:987-991.

How do you create an ABM?

1. Gather relevant informationabout interactive entities (agents).

2. Formulate theories aboutagent behavior.

3. Implement theories in a computer simulation.

4. Observe the behavior of the system,looking for emergent behavior patterns.

How do you know if it works?

Verification: To ensure that the programis doing what you intend it to do.Ex. State diagrams

Validation: To ensure that the model emulates the intended behavior. Ex. Apply a perturbation with a knownconsequence in the “real world”.

Some Universities Teaching Agent-Based Modeling

Argonne National Laboratories RePast

Univ. of Mich., Center for the Study of Complex Systems

Swarm

Humbolt State Univ. and Lang, Railsback and Assoc.

“Pattern-Oriented Modeling”

Swarm

Northwestern Univ. NetLogo

Santa Fe Institute, Computer Sciences complexity

Univ. of Notre Dame, Interdisciplinary Center for the Study of Biocomplexity

complexity

Univ. of Torino, Italy complexity

Univ. of Washington complexity

Univ. of California, Berkeley complexity

Auburn Univ. complexity

The End