1. From Agent-based models to network analysis (and return): the policy-making perspective
Magda Fontana Pietro Terna
University of Torino retired professor of the University of Torino
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

2. ____________________________
A few premises
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

3. AISC-CODISCO 2014, revised Nov.2015
An important perspective use of Agent-based models (ABMs) is that of being employed as tools to support decision systems in policy-making, in the complex systems framework.
Such models can be usefully employed at two different levels: to help in deciding (policy-maker level) and to empower the capabilities of people in evaluating the effectiveness of policies (citizen level).
As a consequence, the class of ABMs for policymaking needs to be both quite simple in its structure and highly sophisticated in its outcomes.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

4. AISC-CODISCO 2014, revised Nov.2015
The pursuing of simplicity and sophistication can be made more efficacious by applying network analysis to the emergent results.
The consequences of choices and decisions and their effects on society, and on its organization, are both relevant.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

5. AISC-CODISCO 2014, revised Nov.2015
Considering together the agent-based and network techniques, we have a further important possibility.
Being easier to have network data (i.e., social network data) than detailed behavioral individual information, we can try to understand the links between the dynamic changes of the networks emerging from agent-based models and the behavior of the agents.
As we understand these links, we can apply them to actual networks, to make guesses about the content of the behavioral black boxes of real-world agents.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

6. ____________________________
How to generate emerging networks to experiment with them
first step
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

7. AISC-CODISCO 2014, revised Nov.2015
recipeWorld is an agent-based model that simulates the emergence of network out of decentralized autonomous interaction.
The rationale behind it is to offer a few hints to find a framework and a grammar that are flexible and straightforward enough to encompass the widest possible range of purposeful and socially meaningful individual and organizational behavior.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

8. AISC-CODISCO 2014, revised Nov.2015
Recipes are coded as strings of numbers – their components. Each number (or, if we want, each label), is related to an act, a sub-routine, of the modeled action.
For instance:
[ ] means:
execute step 3, then
execute step 1, then …
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

9. AISC-CODISCO 2014, revised Nov.2015
Examples in different fields can be suggested:
production,
health-care scenarios,
financial complex operations,
opinion spreading,
co-authorships,
etc.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

10. AISC-CODISCO 2014, revised Nov.2015
Behind any step, we an imagine to have any arbitrary level of complicated actions.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

11. AISC-CODISCO 2014, revised Nov.2015
A simple NetLogo [ ] implementation at
looking at
g_productionWorld.nlogo
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

12. AISC-CODISCO 2014, revised Nov.2015
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

13. AISC-CODISCO 2014, revised Nov.2015
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

14. AISC-CODISCO 2014, revised Nov.2015
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

15. AISC-CODISCO 2014, revised Nov.2015
Calculations are made using the new NW NetLogo extension
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

16. AISC-CODISCO 2014, revised Nov.2015
Calculations are made using the new NW NetLogo extension
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

17. AISC-CODISCO 2014, revised Nov.2015
A less simple SLAPP
[ ] implementation
keep the current SLAPP version and run the ‘production’ example
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

18. AISC-CODISCO 2014, revised Nov.2015
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

19. AISC-CODISCO 2014, revised Nov.2015
What is making “special” this result is that, in this context, agents are activated (following their internal rules and capabilities) by the events.
The network emerges as a side effect, as in the real world.
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

20. ____________________________
How to generate emerging networks:
A - actual entities, B - agents,
C - emerging network
second step
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

21. AISC-CODISCO 2014, revised Nov.2015B A a2 a1 e1 e3 e4 e2 a4 a3 a1 a3 C a2 …
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

22. ____________________________
How to generate emerging networks: now forget A and B and build C from D
and try to go back to the agents (reverse engineering)
third step
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

23. AISC-CODISCO 2014, revised Nov.2015B A a2 a1 e1 e3 e4 e2 a4 a3 a1 a3 C
D ! a2 …
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

24. AISC-CODISCO 2014, revised Nov.2015
B !!
A ? e1 e3 e4 e2 a2 a1 a4 a3 D n1 n3 n4 n2 C a1 a3 a2 …
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

25. ____________________________
How to generate emerging networks: back from the dream to the
currently possible activities
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

26. AISC-CODISCO 2014, revised Nov.2015
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

27. recipeWorld is currently a prototipe in NetLogo
A previous implementation of the recipe idea (without the network side) already exists in Java Swarm; it is at
A new version exists in SLAPP (Swarm-Like Agent Protocol in Python); SLAPP is at
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015

28. Thanks magda.fontana@unito.it and pietro.terna@unito.it
December 3, 2014
AISC-CODISCO 2014, revised Nov.2015