1. March 10 02006 Erb Scott E Page University of Michigan and Santa Fe Institute Complex Systems, Political Science, Economics

2. March 10 02006 Erb Agent Based Modeling The Interest in Between

3. March 10 02006 Erb Outline What it is? A ladder of models A core question The in between Four uses

4. March 10 02006 Erb What is it?

5. March 10 02006 Erb The Spherical Cow

6. March 10 02006 Erb A Whole Lotta Spherical Cows

7. March 10 02006 Erb A New Kind of Science Stephen Wolfram

8. March 10 02006 Erb Wolfram’s 256 Automata N X

9. March 10 02006 Erb Rule 90 N X 2 8 16 64 Sum = 90

10. March 10 02006 Erb Wolfram’s Findings Simple rules can create patterns like those in nature randomness computation Summary: `it from bit’

11. March 10 02006 Erb Conway’s Game of Life X5 76 4 1 23 8 Cell has eight neighbors Cell can be alive Cell can be dead Dead cell with 3 neighbors comes to life Live cell with 2,3 stays alive

12. March 10 02006 Erb Examples X

13. March 10 02006 Erb A ladder of models

14. March 10 02006 Erb Gell Mann’s Version ``Imagine how hard physics would be if electrons could think.”

15. March 10 02006 Erb Model as Metaphor Forest Fires & Bank Failures

16. March 10 02006 Erb Forest Fire Model At each site tree grows with prob p Trees are good, lightening hits w/ prob q Fires spread to neighboring trees

17. March 10 02006 Erb Bank Failure Model Make risky loans each period with prob p Risky loans fail with prob q, but pay more Failures spread to neighboring banks

18. March 10 02006 Erb Example Period 1: OOROOROOORROR Period 2: ROROOROORRRRR

19. March 10 02006 Erb Example Period 1: OOROOROOORROR Period 2: ROROOROORRRRR Period 3: ROROOROOFRRRR Period 4: ROROOROOFFFFFF Period 5: ROROOROOOOOOR

20. March 10 02006 Erb The Bottom Rung: Rule Aggregation

21. March 10 02006 Erb A Phase Transition rate of risky loans yield

22. March 10 02006 Erb The Second Rung: Global Selection

23. March 10 02006 Erb The ‘edge of chaos’ p* yield

24. March 10 02006 Erb The Third Rung: Individual Adaptation

25. March 10 02006 Erb What’s the matter here? p* yield

26. March 10 02006 Erb Emergence of Firewalls 111O11O111O1111OO111

27. March 10 02006 Erb The Top Rung: Optimal behavior

28. March 10 02006 Erb The Optimal Solution 1111011110111101111

29. March 10 02006 Erb We follow routines We select better rules We respond and learn We have it all figured out

30. March 10 02006 Erb We follow routines: laundry We select better rules: where we shop We respond and learn: dating We have it all figured out: tic tac toe

31. March 10 02006 Erb A core question

32. March 10 02006 Erb ``What happens once we define the set of the possible and the rules of the game?’’

33. March 10 02006 Erb Though policy analysis focuses on what happens if, we must also consider what happens if not.

34. March 10 02006 Erb What goes up….

35. March 10 02006 Erb Must come down.

36. March 10 02006 Erb The Business Environment Incentives: unfettered and induced Regulations and restrictions Technological change Information Global climate change Demographic and preference change

37. March 10 02006 Erb The in between

38. March 10 02006 Erb How we answer the core question Thick description (TD) Simple models (SM)

39. March 10 02006 Erb Agent based models enable us to explore the space in between the incredibly rich and complex real world and our stark models. We can explore the attainability of outcomes, the robustness of functionalities, and the path dependence of systems.

40. March 10 02006 Erb ABM can easily (and poorly) include heterogeneity networks and space adaptation feedbacks and lags

41. March 10 02006 Erb Flexibility Logical Consistency TD ABM SM

42. March 10 02006 Erb Four Uses

43. March 10 02006 Erb ABM models complement SIR(S) models by including social networks, transportation systems, and agent level heterogeneity (genotypic and phenotypic) and adaptive responses Math +

44. March 10 02006 Erb ABM models allow us to test the implications of policies. Project SLUCE considered effects of sprawl policies on ecosystems at the exurban fringe. The laboratory

45. March 10 02006 Erb ABM models can be used as test beds for experiments with real people. Differences often minor -- TFT emerged in first experiments with both people and artificial agents. The people alternative

46. March 10 02006 Erb ABM models can be used to explore the implications of assumptions. From them we’ve learned how birds flock, how patterns form, and why some communicable diseases have waves. The intuition builder

47. March 10 02006 Erb Not if ABM, but how? The economics of methodology

48. March 10 02006 Erb This won’t happen by chance