what is agent-based modeling? virginia a. folcik nivar ph.d
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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.
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