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Programming for Social Scientists Lecture 5

Programming for Social Scientists Lecture 5. UCLA Political Science 209-1: Programming for Social Scientists Winter 1999 Lars-Erik Cederman & Benedikt Stefansson. Today's topics. lists of agents random number generators loading parameters from file nested Swarms Example 1: SimpleList

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Programming for Social Scientists Lecture 5

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  1. Programming for Social ScientistsLecture 5 UCLA Political Science 209-1: Programming for Social Scientists Winter 1999 Lars-Erik Cederman & Benedikt Stefansson

  2. Today's topics • lists of agents • random number generators • loading parameters from file • nested Swarms Example 1: SimpleList Example 2: Evol IPD (evolutionary version of SimpleIPD) POL SCI 209-1 Cederman / Stenfansson

  3. Managing many agents • Swarm offers the class Collection • Collections can be of type: • List (today's focus!) • Array (different from arrays in C!) • Keyed Collection (maps and sets) Note: Collections are dynamic data structures that can change during run-time (cf. pointers in C) POL SCI 209-1 Cederman / Stenfansson

  4. Arrays and Linked Lists Array: fast access 3 8 2 5 7 7 1 4 9 2 Linked list: flexibility 2 8 3 5 POL SCI 209-1 Cederman / Stenfansson

  5. Lists in Swarm [list atOffset: 3] list = [List create: self] [list addLast: obj4] obj4 obj2 obj3 obj1 index = [list begin: self] obj=[index next] POL SCI 209-1 Cederman / Stenfansson

  6. SimpleList • Create 10 elements in a linked list • Print them • Repeat 10 times: • Scramble the order • Print the elements again POL SCI 209-1 Cederman / Stenfansson

  7. SimpleList: Sample Output Count: 10 List: 0 1 2 3 4 5 6 7 8 9 Repl 1: 8 2 0 1 4 7 9 3 5 6 Repl 2: 9 0 3 6 5 1 8 2 4 7 ... Repl 10: ... POL SCI 209-1 Cederman / Stenfansson

  8. SimpleList: File Structure Model- Swarm.h Element.h Model- Swarm.m main.m Element.m POL SCI 209-1 Cederman / Stenfansson

  9. SimpleList: main.m #import "ModelSwarm.h" int main(int argc, const char ** argv) { id modelSwarm; initSwarm(argc, argv); modelSwarm = [ModelSwarm create: globalZone]; [modelSwarm buildObjects: 10]; [modelSwarm run]; return 0; } POL SCI 209-1 Cederman / Stenfansson

  10. // Element.h #import <objectbase.h> #import <objectbase/SwarmObject.h> @interface Element: SwarmObject { int name; } -init: (int) n; -(int) getID; @end // Element.m #import "Element.h" @implementation Element -init: (int) n { name = n; return self; } -(int) getID { return name; } @end SimpleList: Element.h/m POL SCI 209-1 Cederman / Stenfansson

  11. SimpleList: ModelSwarm.h #import "Element.h" #import <objectbase.h> #import <objectbase/Swarm.h> #import <random.h> @interface ModelSwarm: Swarm { id objList; } +createBegin: (id) aZone; -createEnd; -buildObjects: (int) n; -printObjects: list; -shuffle: list; -run; @end POL SCI 209-1 Cederman / Stenfansson

  12. #import "ModelSwarm.h" @implementation ModelSwarm +createBegin: (id) aZone { ModelSwarm * obj; obj = [super createBegin: aZone]; return obj; } -createEnd { return [super createEnd]; } -buildObjects: (int) n { int i; id anElement; objList = [List create:self]; for (i=0; i<n; i++) { anElement = [Element create: self]; [anElement init: i]; [objList addLast: anElement]; } return self; } SimpleList: ModelSwarm.m (1) POL SCI 209-1 Cederman / Stenfansson

  13. SimpleList: ModelSwarm.m (2) -printObjects: list { id index, anElement; index = [list begin: self]; while ((anElement=[index next])) printf("%d ", [anElement getID]); [index drop]; printf("\n"); return self; } POL SCI 209-1 Cederman / Stenfansson

  14. SimpleList: ModelSwarm.m (3) -shuffle: list { int j, k; id temp; j = [list getCount]; while (j>1) { k = [uniformIntRand getIntegerWithMin: 0 withMax: j-1]; j--; temp = [list atOffset: k]; [list atOffset: k put: [list atOffset: j]]; [list atOffset: j put: temp]; } return self; } POL SCI 209-1 Cederman / Stenfansson

  15. SimpleList: ModelSwarm.m (4) -run { int randomSeed; printf("Count: %d\n", [objList getCount]); printf("List: "); [self printObjects: objList]; for (randomSeed=1; randomSeed<=10; randomSeed++) { [randomGenerator setStateFromSeed: randomSeed]; [self shuffle: objList]; printf("Repl %2d: ", randomSeed); [self printObjects: objList]; } return self; } @end POL SCI 209-1 Cederman / Stenfansson

  16. getCount Gives number of members atOffset: i Retrieves member at location i atOffset:i put: obj Inserts obj at location i addFirst: o addLast: o Adds o at start/end of list getFirst,getLast Returns first/last member contains: o Returns 1 if o is member remove: o Removes object o removeAll Removes all forEach:M(message) Sends message to all members removeFirst/Last removes and returns first/last member Some Collection syntax POL SCI 209-1 Cederman / Stenfansson

  17. Any collection can generate an index of itself The index behaves as an object, and understands messages such as: prev,next findNext: o,findPrev: o Using index to loop over all members: index=[list begin: zone]; while(o=[index next]) value=[o getValue]; [index drop]; Accessing Collections with Index POL SCI 209-1 Cederman / Stenfansson

  18. Typical use of a List instance is to keep track of agent population At create time Model initializes each agent and puts him on agentList The agentList is then accessed by Schedule, GUI objects and so on... Example for(i=0;i<numAgents;i++) { a=[Agent create: zone]; [a setVar1: var1]; [a setVar2: var2]; ... [a setVarN: varN]; [agentList addLast: a]; } Typical use of List POL SCI 209-1 Cederman / Stenfansson

  19. To draw random numbers from a distribution you’ll need a generator random seed - an integer number which primes the generator a distribution Generating Random Numbers Generator a seed Distribution random sequence of numbers POL SCI 209-1 Cederman / Stenfansson

  20. When calling initSwarm in main, three default distributions are generated, fed by a default generator It is also possible to choose other generators and distributions by using the Random library (more about that later...) Default distributions Uniform Integer MT19937 Generator Uniform Unsigned Integer Uniform Double POL SCI 209-1 Cederman / Stenfansson

  21. Using the default distributions • Default distributions are global • Can call any distribution from any agent • For a double in interval [minVal, maxVal]: [uniformDblRand getDoubleWithMin: minVal withMax: maxVal]; • For an integer in interval [minVal, maxVal]: [uniformIntegerRand getDoubleWithMin: minVal withMax:maxVal]; • To set the seed to Val: [randomGenerator setStateFromSeed: Val]; POL SCI 209-1 Cederman / Stenfansson

  22. Looking up documentation Main resource: http://www.santafe.edu/projects/swarm/ Reference manual: e.g. Collections, Random libraries; see also index See e.g. Collection [p. 94]: Name Collection Description ... Protocols adopted by Collection: Create, ... Copy, Drop... Methods Phase: Creating Phase: Using -(BOOL)getCount -(BOOL)contains: aMember POL SCI 209-1 Cederman / Stenfansson

  23. To manage more than two players we add a playerList Tournament is a nested swarm letting two agents play IPD Evol IPD main ModelSwarm popList Tournament winner newList POL SCI 209-1 Cederman / Stenfansson

  24. Riolo's GA algorithm in pseudo-code (see Sci. Am.) while (NewPopNotFull) { i=random()/PopSize; j=random()/PopSize; if (URand01() < 0.75) Copy most fit of Pop[i],Pop[j] to NewPop else Copy least fit of Pop[i],Pop[j] to NewPop; } Pop = NewPop; POL SCI 209-1 Cederman / Stenfansson

  25. Player.h Player.m Evol IPD: File Structure Tourna- ment.h Model- Swarm.h Model- Swarm.m Tourna- ment.m main.m POL SCI 209-1 Cederman / Stenfansson

  26. Evol IPD: main.m #import <simtools.h> #import "ModelSwarm.h" int main(int argc, const char ** argv) { id modelSwarm; initSwarm(argc, argv); modelSwarm = [ModelSwarm create: globalZone]; [modelSwarm buildObjects]; [modelSwarm run]; return 0; } POL SCI 209-1 Cederman / Stenfansson

  27. Evol IPD: ModelSwarm.h #import "Player.h" #import "Tournament.h" #import <objectbase.h> #import <objectbase/SwarmObject.h> #import <space.h> #import <activity.h> #import <random.h> @interface ModelSwarm: Swarm { id popList,newList; int numGen, randomSeed; int numPlayers, num[4], n0, n1, n2, n3; double selectionPressure; } +createBegin: (id) aZone; -createEnd; -buildObjects; -runTournament; -reportResults: (int)gen; -run; @end POL SCI 209-1 Cederman / Stenfansson

  28. Evol IPD: ModelSwarm.m (1) #import "ModelSwarm.h" #import <simtools.h> @implementation ModelSwarm +createBegin: (id) aZone { ModelSwarm * obj; obj = [super createBegin: aZone]; obj->numGen = 10; return obj; } -createEnd { [ObjectLoader load: self fromFileNamed: "model.setup"]; return [super createEnd]; } POL SCI 209-1 Cederman / Stenfansson

  29. -buildObjects { id aPlayer; int pt,i; [randomGenerator setStateFromSeed: randomSeed]; time = 0; num[0] = n0; num[1] = n1; num[2] = n2; num[3] = n3; numPlayers = n0+n1+n2+n3; popList = [List create: self]; newList = [List create: self]; for (pt = 0; pt < 4; pt++) for (i = 0; i < num[pt]; i++) { aPlayer = [Player createBegin: self]; [aPlayer setPlayerType: pt]; aPlayer = [aPlayer createEnd]; [popList addLast: aPlayer]; } return self; } Evol IPD: ModelSwarm (2) POL SCI 209-1 Cederman / Stenfansson

  30. Evol IPD: ModelSwarm.m (3) -runTournament { id tournament; id tempList; id player1, player2, survivor, newPlayer; int i, p1, p2; for (i=0; i<numPlayers; i++) { p1 = [uniformIntRand getIntegerWithMin: 0 withMax: numPlayers-1]; p2 = [uniformIntRand getIntegerWithMin: 0 withMax: numPlayers-1]; player1 = [popList atOffset: p1]; player2 = [popList atOffset: p2]; tournament = [Tournament createBegin: self]; [tournament setPlayer1: player1 Player2: player2]; [tournament createEnd]; [tournament run]; // for loop cont'd POL SCI 209-1 Cederman / Stenfansson

  31. Evol IPD: ModelSwarm.m (4) if ([uniformDblRand getDoubleWithMin: 0.0 withMax: 1.0] < selectionPressure) survivor=[tournament getWinner]; else survivor=[tournament getLoser]; newPlayer=[Player create: self]; [newPlayer initPlayerType: [survivor getPlayerType]]; [newList addLast: newPlayer]; } [tournament drop]; [popList deleteAll]; // Swapping lists tempList = popList; popList = newList; newList = tempList; return self; } POL SCI 209-1 Cederman / Stenfansson

  32. Evol IPD: ModelSwarm.m (5) -reportResults: (int) gen { id index; id aPlayer; int pt; for (pt=0; pt<4; pt++) num[pt] = 0; index = [popList begin: self]; while((aPlayer=[index next])) num[[aPlayer getPlayerType]]++; [index drop]; printf("Time: %4d Num: %6d %6d %6d %6d\n", gen, num[0], num[1], num[2], num[3]); return self; } POL SCI 209-1 Cederman / Stenfansson

  33. Evol IPD: ModelSwarm.m (6) -run { int gen; [self reportResults: 0]; for (gen = 1; gen <= numGen; gen++) { [self runTournament]; [self reportResults: gen]; } return self; } @end POL SCI 209-1 Cederman / Stenfansson

  34. Evol IPD: Tournament.h #import "Player.h" #import <objectbase.h> #import <objectbase/Swarm.h> #import <space.h> #import <activity.h> @interface Tournament: Swarm { id player1, player2; int numIter; } +createBegin: (id) aZone; -createEnd; -setPlayer1: p1 Player2: p2; -updateMemories; -distrPayoffs; -(id)getWinner; -(id)getLoser; -run; @end POL SCI 209-1 Cederman / Stenfansson

  35. ... @implementation Tournament ... -setPlayer1: p1 Player2: p2 ... -updateMemories... -distrPayoffs... -(id)getWinner { int winner; if ([player1 getPayoff] > [player2 getPayoff]) winner = player1; else winner = player2; return winner; } -(id)getLoser... -run { int time; numIter = 4; [player1 setPayoff: 0]; [player2 setPayoff: 0]; for (time=0; time<numIter; time++) { [self updateMemories]; [player1 step: time]; [player2 step: time]; [self distrPayoffs]; } return self; } Evol IPD: Tournament.m POL SCI 209-1 Cederman / Stenfansson

  36. ... int iParam[4] = {1, 1, 0, 0}; int pParam[4] = {1, 1, 0, 0}; int qParam[4] = {1, 0, 1, 0}; @implementation Player -setPlayerType: (int) pt { type = pt; return self; } -(int) getPlayerType { return type; } ... -step: (int) time { if (time==0) newAction = iParam[type]; else { if (memory==1) newAction = pParam[type]; else newAction = qParam[type]; }; return self; } @end Evol IPD: Player.m POL SCI 209-1 Cederman / Stenfansson

  37. Loading/Saving state • ObjectLoader • Reads values of ivars from file • ObjectSaver • Writes values of ivars to file • Any instance vars not mentioned in infile unchanged • The model.setup file: @begin randomSeed 8251777 selectionPressure 0.75 numGen 15 n0 64 n1 64 n2 64 n3 64 @end • ObjectLoader needs • target object • name of file [ObjectLoader load: self fromFileNamed:"model.setup"]; POL SCI 209-1 Cederman / Stenfansson

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