1. May 9-11, 2004SwarmFest, CSCS, University of Michigan 1 jESevol Pietro Terna pietro.terna@unito.it Department of Economics and Finance “G.Prato” University of Torino - Italy Evolving a simulated system of enterprises with jESevol and Swarm web.econ.unito.it/terna web.econ.unito.it/terna/jes

2. May 9-11, 2004SwarmFest, CSCS, University of Michigan 2 _jES->jESlet and jESevol _______________________________________ jES jESlet and jESevol _______________________________________

3. May 9-11, 2004SwarmFest, CSCS, University of Michigan 3 From jES … jVE->jES java Enterprise Simulator … to jESlet (with a didactic goal) and … … to jESevol, to simulate an evolving system of enterprises

4. May 9-11, 2004SwarmFest, CSCS, University of Michigan 4 _overview _______________________________________ Overview _______________________________________

5. May 9-11, 2004SwarmFest, CSCS, University of Michigan 5 overview 1 Overview 1/2 From jES (our java Enterprise Simulator), we have derived jESevol, or “Evolutionary java Enterprise Simulator”. jES is a large Swarm-based package[1] aimed at building simulation models both of actual enterprises and of virtual ones. jESevol simulates systems of enterprises or production units in an evolutionary context, where new ones arise continuously and some of the old are dropped out. Our environment is a social space with metaphorical distances representing trustiness and cooperation among production units (the social capital). The production is represented by a sequence of orders; each order contains a recipe, i.e. the description of the sequence of activities to be done by several units to complete a specific production. [1] Download last versions of jES, jESlet and jESevol from http://web.econ.unito.it/terna/jes

6. May 9-11, 2004SwarmFest, CSCS, University of Michigan 6 overview 2 Overview 2/2 Two units can cooperate in the production process only if they are mutually visible in our social network. Units that do not receive a sufficient quantity of orders, as well as the ones that cannot send the accomplished orders to successive units, disappear. New enterprises arise, in the attempt of filling the structural holes (Burt, 1992; Walker et al., 1997) of our social network. A complex structure emerges from our environment, with a difficult and instable equilibrium whenever the social capital is not sufficient. References Burt R.S. (1992), Structural Holes – The Social Structure of Competition. Cambridge, MA, Harvard University Press. Walker G., Kogut B., Shan W. (1997), Social Capital, Structural Holes and the Formation of an Industry Network, in Organization Science. Vol. 8, No. 2, pp.109-25.

7. May 9-11, 2004SwarmFest, CSCS, University of Michigan 7 evolving system We look at an incomplete production system continuously adapting itself to the reality coming from the global demand of the market … … while new firms arise and old ones are dropped off To produce goods, supply chains are created and modified, according to the changes in exiting firms

8. May 9-11, 2004SwarmFest, CSCS, University of Michigan 8 _jES basics _______________________________________ jES basics _______________________________________

9. May 9-11, 2004SwarmFest, CSCS, University of Michigan 9 WD, DW, WDW WD side or formalism: What to Do DW side or formalism: which is Doing What WDW formalism: When Doing What Three formalisms

10. May 9-11, 2004SwarmFest, CSCS, University of Michigan 10 dictionary unit= a productive structure; a unit is able to perform one of the steps required to accomplish an order order= the object representing a good to be produced; an order contains technical information (the recipe describing the production steps) recipe=a sequence of steps to be executed to produce a good A dictionary

11. May 9-11, 2004SwarmFest, CSCS, University of Michigan 11 _A flexible scheme _______________________________________ A flexible scheme in jESevol _______________________________________

12. May 9-11, 2004SwarmFest, CSCS, University of Michigan 12 DW: a flexible scheme Units … DW … on a toroidal space (left and right borders and top and bottom ones are close together) 2 13 2 1 4 5 3 1 Each unit is able to do a specific step …

13. May 9-11, 2004SwarmFest, CSCS, University of Michigan 13 WD: recipes WD with the recipes of the orders (what to do) expressed as sequences of numbers; orders with recipes are randomly generated with different lengths and structures 1 3 2 4 5 3 4 3 5 1 1 … … of a recipe

14. May 9-11, 2004SwarmFest, CSCS, University of Michigan 14 moving recipes DW and WD 2 13 2 1 4 5 3 1 1 3 2 4 moving around among units 1 3 2 4 ? lack of visibility how to choose Visibility is a metaphorical representation of trustiness and cooperation in a social network; when global visibility increases, we have more “social capital”

15. May 9-11, 2004SwarmFest, CSCS, University of Michigan 15 visibility and … visibility changes new units appear randomly (enterprise creation) with strategic relationships … … or alone some units are dropped out Visibility increases with the time (initial visibility is randomly chosen)

16. May 9-11, 2004SwarmFest, CSCS, University of Michigan 16 … bars The left (blue) bar of each unit reports the number of waiting orders (do be done) The down bar of each unit reports the number of consecutive clock ticks in which the unit has been idle If > maxInactivity the unit is dropped out and all unsent products are lost The right (red) bar of each unit reports the number of unsent products, due to the fact that a unit able to do the required step does not exist or is not visible If > maxUnsentProducts the unit is dropped out and all unsent and waiting products are lost

17. May 9-11, 2004SwarmFest, CSCS, University of Michigan 17 _an introductory case _______________________________________ An introductory case, robust and fragile _______________________________________

18. May 9-11, 2004SwarmFest, CSCS, University of Michigan 18 the parameters, robust introductory case potentialUnitTypes 5 unitGenerationInitialP 1 potentialUnitNumberPerType 2 newUnitGenerationP 0.0 interVisibilityMinLevel 0 increasingVisibilityStep 0.0 maxInactivity 10 maxUnsentProducts 10 max n. of types and max presence per type, here 5 * 2 with p=1 p of a new unit in each cycle, with a random type in this basic case all units are visible and visibility does not change we assume that an actual firm is dropped out from the market after three months of inactivity, so 10 ticks = 3 months of history similarly … Why 10? Our recipes have here maxStepNumber =5 and maxStepLength=2; potentially, in 10 ticks, each unit can receive an order, but only as a limit case; with this parameters the system can be exposed to a complete crash Introductory robust case

19. May 9-11, 2004SwarmFest, CSCS, University of Michigan 19 introductory case: robust case 1,000 ticks = 25 years of actual time only 5 units kept alive global/potential PRODUCTION final/potential final/global Introductory robust case

20. May 9-11, 2004SwarmFest, CSCS, University of Michigan 20 the parameters, fragile introductory case potentialUnitTypes 10 unitGenerationInitialP 1 potentialUnitNumberPerType 1 newUnitGenerationP 0.0 interVisibilityMinLevel 0 increasingVisibilityStep 0.0 maxInactivity 10 maxUnsentProducts 10 Our recipes have here maxStepNumber 10 and maxStepLength 1 Introductory fragile case max n. of types and max presence per type, here 10 * 1 with p=1

21. May 9-11, 2004SwarmFest, CSCS, University of Michigan 21 introductory case: fragile case 150 ticks < 4 years of actual time no units kept alive global/potential PRODUCTION final/potential final/global Basic fragile case

22. May 9-11, 2004SwarmFest, CSCS, University of Michigan 22 _a study case __________________________________________________ A study case, with 3 versions: (i) basic, (ii) increasing social capital, (iii) with greater financial intervention of the banking system __________________________________________________

23. May 9-11, 2004SwarmFest, CSCS, University of Michigan 23 the parameters, basic study case potentialUnitTypes 5 unitGenerationInitialP 0.8 potentialUnitNumberPerType 2 newUnitGenerationP 0.8 interVisibilityMinLevel 1 increasingVisibilityStep 5 maxInactivity 10 maxUnsentProducts 10 max n. of types and max presence per type, here 5 * 2 with p=0.8 p of a new unit in each cycle, with a random type in this study case, min visibility is 1, i.e. at least one common patch; visibility increases of 5 patches in each tick (i) basic study case, starter file 5 in jESevol 0.3.00 Our recipes have here maxStepNumber 5 and maxStepLength 2

24. May 9-11, 2004SwarmFest, CSCS, University of Michigan 24 study case: basic 1,000 ticks = 25 years of actual time a relevant variability in the number of units (social costs), with the trace of a cycle global/potential PRODUCTION final/potential final/global (i) basic study case, starter file 5 in jESevol 0.3.00 a medium performance in term of potential production some form of structure seems to emerge

25. May 9-11, 2004SwarmFest, CSCS, University of Michigan 25 the parameters, increasing social capital study case potentialUnitTypes 5 unitGenerationInitialP 0.8 potentialUnitNumberPerType 2 newUnitGenerationP 0.8 interVisibilityMinLevel 1 increasingVisibilityStep 10 maxInactivity 10 maxUnsentProducts 10 max n. of types and max presence per type, here 5 * 2 with p=0.8 p of a new unit in each cycle, with a random type in this study case, min visibility is 1, i.e. at least one common patch; visibility increases of 10 patches in each tick (ii) Increasing social capital study case, starter file 5.2 in jESevol 0.3.00 Our recipes have here maxStepNumber 5 and maxStepLength 2

26. May 9-11, 2004SwarmFest, CSCS, University of Michigan 26 study case: increasing social capital 1,000 ticks = 25 years of actual time a relevant variability in the number of units (social costs), but now with an evident cycle global/potential PRODUCTION final/potential final/global a good (and increasing) performance in term of potential production evident structures emerge (ii) Increasing social capital study case, starter file 5.2 in jESevol 0.3.00

27. May 9-11, 2004SwarmFest, CSCS, University of Michigan 27 the parameters, bank system study case potentialUnitTypes 5 unitGenerationInitialP 0.8 potentialUnitNumberPerType 2 newUnitGenerationP 0.8 interVisibilityMinLevel 1 increasingVisibilityStep 5 maxInactivity 15 maxUnsentProducts 10 in this study case, min visibility is 1, i.e. at least one common patch; visibility is increases of 5 patches in each tick (iii) Greater financial intervention of the banking system study case, starter file 5.3 in jESevol 0.3.00 Our recipes have here maxStepNumber 5 and maxStepLength 2 we assume that an actual firm is dropped out from the market after 15 ticks of inactivity, instead of 10

28. May 9-11, 2004SwarmFest, CSCS, University of Michigan 28 study case: bank system study case 1,000 ticks = 25 years of actual time a less relevant variability in the number of units (reduced social cost)s, always with an evident cycle global/potential PRODUCTION final/potential final/global a good performance in term of potential production evident structures emerge (iii) Greater financial intervention of the banking system study case, starter file 5.3 in jESevol 0.3.00

29. May 9-11, 2004SwarmFest, CSCS, University of Michigan 29 Stability; perspectives Stability Cases i, ii and iii are stable also running them for 4,000 ticks (one century)! Short term enhancements A lot of investigation is necessary on cases (i), (ii) and (iii) modelling explicitly the banking system, with the concurrent effects of the cases of bankruptcy in firms and banks Using a Genetic Algorithm tool to choose units to be created at each tick and where to place them; the fitness will be generated by jESevol itself, from different points of view: the whole economic system, a specific unit, a cluster of units, …

30. May 9-11, 2004SwarmFest, CSCS, University of Michigan 30 address again pietro.terna@unito.it web.econ.unito.it/terna web.econ.unito.it/terna/jes Let run case 5.2 or 5.3 at the question time!