1. Looking
for
a
bridge
between
approaches

2. Global
knowledge
A
bridge
for
what?
Local
knowledge

3. Global
knowledge
Structured
InformaHon
HOW
IS
THE
CURRENT
BRIDGE?
Tacit
Knowledge
Local
knowledge

4. Global
knowledge
Structured
InformaHon
Organized
knowledge
HOW
IS
THE
CURRENT
BRIDGE?
Tacit
Knowledge
Disintegrated
policies
Local
knowledge

5. Global
knowledge
Structured
InformaHon
Organized
knowledge
Why
is
this
so?
Tacit
Knowledge
Disintegrated
policies
Local
knowledge

6. Formalizing
Dynamics
DEEP
Formalizing
Associa1ons
SHALLOW
Policy
Modeling
• System
of
Variables
(dependent
–
independent)
• Linear
relaHon
• Hierarchical
organizaHon
• Homogeneity
assumpHons
• Scare
of
Ecological
Fallacy
Mainstream
Policy
Science
Global
knowledge
Structured
InformaHon
Organized
knowledge
Why
is
this
so?
Tacit
Knowledge
Disintegrated
policies
Local
knowledge

7. DEEP
Formalizing
Associa1ons
SHALLOW
Policy
Modeling
• System
of
Variables
(dependent
–
independent)
• Linear
relaHon
• Hierarchical
organizaHon
• Homogeneity
assumpHons
• Scare
of
Ecological
Fallacy
Mainstream
Policy
Science
Global
knowledge
Structured
InformaHon
Organized
knowledge
Why
is
this
so?
Tacit
Knowledge
Disintegrated
policies
Local
knowledge
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior
But…
Formalizing
Dynamics

8. DEEP
Formalizing
Associa1ons
SHALLOW
Policy
Modeling
Can
we
reconcile
this?
• System
of
Variables
(dependent
–
independent)
• Linear
relaHon
• Hierarchical
organizaHon
• Homogeneity
assumpHons
• Scare
of
Ecological
Fallacy
Mainstream
Policy
Science
Global
knowledge
Structured
InformaHon
Tacit
Knowledge
Organized
knowledge
Disintegrated
policies
Local
knowledge
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior
But…
Formalizing
Dynamics

9. Formalizing
Dynamics
DEEP
Policy
Modeling
Can
we
reconcile
this?
Global
knowledge
Organized
knowledge
Tacit
Knowledge
Local
knowledge
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

10. Policy
Modeling
Global
knowledge
DEEP
A
computaHonal
bridge!
Formalizing
Dynamics
Path-­‐
dependence
Localized
Organized
knowledge
Rules
AGENT-­‐BASED
MODELING
Tacit
Knowledge
Learning
and
adapta,on
Local
knowledge
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

11. BASIC
IDEA:
• RaHonally-­‐
bounded
• PercepHon
• Knowledge
• Response
We
program
agents.
Formalizing
Dynamics
Path-­‐
dependence
Localized
Rules
AGENT-­‐BASED
MODELING
Tacit
Knowledge
•
•
•
•
Organized
knowledge
Learning
and
adapta,on
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

12. BASIC
IDEA:
Formalizing
Dynamics
Path-­‐
dependence
Localized
We
can
have
mulHple
agents
Rules
AGENT-­‐BASED
MODELING
Tacit
Knowledge
•
•
•
•
Organized
knowledge
Learning
and
adapta,on
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

13. BASIC
IDEA:
MULTIPLE
LEVELS
Formalizing
Dynamics
Path-­‐
dependence
Localized
Organized
knowledge
Rules
AGENT-­‐BASED
MODELING
Tacit
Knowledge
Learning
and
adapta,on
We
can
have
mulHple
agents
MULTIPLE
INTERACTIONS
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

14. BASIC
IDEA:
MULTIPLE
LEVELS
Formalizing
Dynamics
Path-­‐
dependence
Localized
TRAJECTORIES
AND
SCALES
Organized
knowledge
Rules
AGENT-­‐BASED
MODELING
Tacit
Knowledge
Learning
and
adapta,on
We
can
have
mulHple
agents
MULTIPLE
INTERACTIONS
•
•
•
•
Networks
of
Actors
Feedback
relaHons
Emergent
organizaHon
Heterogeneity
of
behavior

15. GREAT
APPROACH…
but
challenging
COMPUTING
?
PROGRAMMING
?
COMPUTABILITY
DECOMPOSABILITY
ABSTRACTION
INTEREST
VALIDITY
?
?
DECIDABILITY

16. Hands
on!
PLEASE,
GO
TO:
hYp://climatechangejm.blogspot.com/

17. DISCUSSION
How
do
you
think
ABM
could
face
these
issues?
• Human
Agency
(Hassan,
2009;
Crate
&
Nutall,
2009)
• History
and
Heterogeneity
maYer
(Rosen,
2003)
• Scale
(Strauss
&
Orlove,2003;
Rosen,
2003)
• Individual
PercepHon
and
Strategic
responses
(Rosen,2003)
• Tractability
of
climate
change
(Rayner,2003;
Hassan,
2009)
• JusHce
(Crate
&
Nutall,
2009)

18. CLOSING
COMMENTS
How
can
a
simulaHon
ever
tell
us
anything
that
we
do
not
already
know?
HOLDING
THAT:
1.
A
simulaHon
is
no
beYer
than
the
assumpHons
built
into
it.
2.
A
computer
can
do
only
what
it
is
programmed
to
do.
SPACE
OF
DERIVED
POSSIBILITIES
?
Correct
Reasoning
Correct
Reasoning
Correct
Premises
Correct
Premises
ASSUMPTIONS
ASSUMPTIONS

19. CLOSING
COMMENTS
How
can
a
simulaHon
ever
tell
us
anything
that
we
do
not
already
know?
HOLDING
THAT:
1.
A
simulaHon
is
no
beYer
than
the
assumpHons
built
into
it.
2.
A
computer
can
do
only
what
it
is
programmed
to
do.
MODELING
THE
POORLY
UNDERSTOOD
Sufficient
Concepts
Sufficient
Concepts
Relevant
relaHonships
Relevant
relaHonships
Minimal
properHes
Minimal
properHes