AADRL - Workshop 2 team 2 A.A. 2020/21 by Jonathan.Zisser

ENCODED BEHAVIOUR 200 Lines of Code and a Video

Instructor - Shajay Bhooshan Cheolyoung Park | Jamil Al Bardawil | Jonathan Zisser | Pin-ju Wang

TABLE OF CONTENTS INTRODUCTION: ENCODED BEHAVIOUR

CHAPTER 1: ATTRACT/REPULSE, FORCE TRACE AND GRID BASED BEHAVIOUR

CHAPTER 2: FLOCKING AND PATH FOLLOWING

CHAPTER 3: STIGMERGY

CHAPTER 4: MESH GENERATION

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

ENCODED BEHAVIOR Through the exploration of coding and programming, we tested how a particle with no intelligence could be converted into an object with behavior and intelligent movement. What was achieved in this workshop was a set of explorations of multiple sets of behaviors and settings of forces on single and sets of particles and how the changing of behavioral attributes even in small amounts on certain parameters could impact the entire simulation. The simulations started with based behavioral control on a low quantity set of particles and then the exploration moves into defined patterns which are inspired by nature like flocking and stigmergy as well as some force field manipulations and as shown below, each chapter will exhibit what was used as far as parameters to achieve each behavior as well as the changing behaviors correlating to the changing parameters. In most of our scripts, it mainly consist of the following parameter: 1 - The position(p), which defines the location of the agent, and the velocity(v) which defines the speed and direction of the agent. 2 - The range of vision (RangeofVis), according to which the agents can sense their surrounding and sense each other. 3 - Upon sensing each other, the agents can act in different ways: They can collide(coh), separate(sep), wander(wan), align(ali), or follow each others trails.(tra) The above parameters are local rules, which when changed could provide a coherent smart system of the swarming behavior. The main objective of the scripts below are the following: -To change the local parameter (bottom-up design approach), learn and possibly create stigmergy patterns. Therefore, each script has a unique factor for the range of vision, the number of agents, and starting points of these agents. The agents also are given different velocities and forces. Moreover, the cohesion, separation, alignment, and wander vectors are also manipulated in many of the codes to provide possible different interesting combinations. In some of the codes, the types of agents change according to a specific set of rules which are defined.

4 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 5

CHAPTER 1: ATTRACT/REPULSE, FORCE TRACE AND GRID BASED BEHAVIOUR

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

ATTRACT AND REPULSE LOGIC Attract and repulse is a study of force fields applied on a set of particles. Different outcomes can be achieved through the alteration of parameters below: -Rates of repulsion and attraction of the core controllers -Rates of repulsion and attraction amongst the particles The simulations exhibit the behavior of the particles when such force fields are applied, also the different results of patterns when the force fields and the class particle properties are manipulated.

TYPE 1

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particle number: 500 attraction range: 0 repulsion range: 20

particle number: 500 attraction range: 30 repulsion range: 20

particle number: 1500 attraction range: 30 repulsion range: 20

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TYPE 6

particle number: 200 attraction range: 30 repulsion range: 20

particle number: 500 attraction range: 30 repulsion range: 0

particle number: 500 attraction range: 40 repulsion range: 20

DIAGRAM

8 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 9

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 1

TYPE 2

CODE

Particle number of 500 and repulsion magnitude of 0.2 and attraction magnitude of 2.5 are given as fixed variables.

The parameters of this code are:

for (int i = 0; i < totalNum; i += 1) { float d = pos. quareDistanceTo(chargePoints[i]); if (d < 1e-6) continue; dir += ((chargePoints[i] - pos) / d) * -1; }

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and

for (int i = 0; i < totalNum; i += 1) { float d = pos. squareDistanceTo(allStoredPoints[i].pos); if (d < 1e-6) continue; if (d < 5 * 5) dir += ((allStoredPoints[i].pos - pos) / d) * -1; }

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The agents are affected by the attraction and repulsion range of the core controllers

The agents are affected by the attraction and repulsion range of the core controllers attraction range: 0 repulsion range: 20 trail size: 200

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attraction range: 30 repulsion range: 20 trail size: 200 Frame 243

10 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 11

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 3

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CODE

Particle number of 1500 and repulsion magnitude of 0.2 and attraction magnitude of 2.5 are given as fixed variables.

Particle number of 200 and repulsion magnitude of 0.2 and attraction magnitude of 2.5 are given as fixed variables.

The parameters of this code are:

for (int i = 0; i < totalNum; i += 1) { float d = pos. quareDistanceTo(chargePoints[i]); if (d < 1e-6) continue; dir += ((chargePoints[i] - pos) / d) * -1; }

and

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for (int i = 0; i < totalNum; i += 1) { float d = pos. squareDistanceTo(allStoredPoints[i].pos); if (d < 1e-6) continue; if (d < 5 * 5) dir += ((allStoredPoints[i].pos - pos) / d) * -1; } The agents are affected by the attraction and repulsion range of the core controllers attraction range: 30 repulsion range: 20 trail size: 200

12 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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and for (int i = 0; i < totalNum; i += 1) { float d = pos. squareDistanceTo(allStoredPoints[i].pos); if (d < 1e-6) continue; if (d < 5 * 5) dir += ((allStoredPoints[i].pos - pos) / d) * -1; }

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The agents are affected by the attraction and repulsion range of the core controllers attraction range: 30 repulsion range: 20 trail size: 200

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 13

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 5

TYPE 6

CODE

Particle number of 500 and repulsion magnitude of 0.2 and attraction magnitude of 2.5 are given as fixed variables.

The parameters of this code are:

for (int i = 0; i < totalNum; i += 1) { float d = pos. quareDistanceTo(chargePoints[i]); if (d < 1e-6) continue; dir += ((chargePoints[i] - pos) / d) * -1; }

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for (int i = 0; i < totalNum; i += 1) { float d = pos. quareDistanceTo(chargePoints[i]); if (d < 1e-6) continue; dir += ((chargePoints[i] - pos) / d) * -1; }

and

for (int i = 0; i < totalNum; i += 1) { float d = pos. squareDistanceTo(allStoredPoints[i].pos); if (d < 1e-6) continue; if (d < 5 * 5) dir += ((allStoredPoints[i].pos - pos) / d) * -1; }

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The agents are affected by the attraction and repulsion range of the core controllers

attraction range: 30 repulsion range: 0 trail size: 200

attraction range: 40 repulsion range: 20 trail size: 200 Frame 199

14 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 15

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

FORCE TRACE DIAGRAMS

LOGIC By setting a relationship between Particles points and Charging points a curvilinear movement is created. The Charging points can be either attractive or repulsive with respect to Particle points. Thus, choreography of movements leads to different behaviors according to different settings. In this code, the key press features have been added in order to have greater control on chronology and directions of moving points.

REPULSE

ATTRACT

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

CODE Class moving points(); Add Force NearestNeighbor(); Add Force ElectricCharge(); else if ..(compute == #num of point) Add Force Repulsion(); Reset();

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KEY PRESS ‘A’

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addForce_ElectricCharge: *10 Repulse: 2

KEY PRESS ‘D’

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addForce_ElectricCharge: *5 Repulse: 2

18 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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KEY PRESS ‘D’ addForce_ElectricCharge: *5 Repulse: 2

KEY PRESS ‘S’

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addForce_ElectricCharge: *7.5 Repulse: 2

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KEY PRESS ‘A’

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addForce_ElectricCharge: *10 Repulse: 2

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 19

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

GRID BASED BEHAVIOUR LOGIC

DIAGRAMS

The Grid is a feedback mechanism simulating an enviorment in which Class of Particles behave under different forces. Particles affect the environment by creating chemical reactions whenever they collide withe the Chemichal Grid. Sabsequently, the chemicals affect the direction of neighbour particles , later a point in time. the direction which has the higher amount of chemical created will be the most likely by the Particles to take, as more attracting forces are applied. (thus, the shortest path is chosen because it is the one who is less affected by degeradation of chemichal emmitted - the Particles more frequently renew the chemical created in the shortest path).

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nearest attraction: 0 repulse: 1.75 self repulse: 0

nearest attraction: 0 repulse: 1.75 self repulse: 0.1

nearest attraction: 1.35 repulse: 1.75 self repulse: 0

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TYPE 6

nearest attraction: 1.75 repulse: 1.35 self repulse: 0

nearest attraction: 0.5 repulse: 0 self repulse: 1.5

nearest attraction: 0.7 repulse: 0.6 self repulse: 0.6

CODE Class Chem_Grid(); Class Particles(); Void Check points inside cells(); For (...) {map value} Add Force Chem_Grid();

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 21

CHAPTER 2: FLOCKING AND PATH FOLLOWING

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

FLOCKING LOGIC Flocking is the behavior exhibited when a group of particles, called a flock, are foraging or in flight. It is considered an emergent behavior arising from simple rules that are followed by individuals and does not involve any central coordination where each particle takes position in relation to the position of the next one. The parameters that are used for the simulation are: alignment, repulse rate, cohesion rate and number of particles. The agents follow the following rules: -If a corner, be attracted to the three other corners very slightly. -If not a corner, be attracted to the two closest corners with great, but equal, strength. That is, the output force vector of this rule is the sum of two vectors of magnitude f. Note that when an agent is on the line formed by its two closest corners, the forces cancel each other out. -Avoid any agents that get too close.

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particle number: 700 alignment value: 1 separation value: 0.12 cohesion value: 0.15

particle number: 500 alignment value: 0.8 separation value: 0.5 cohesion value: 0.15

particle number: 300 alignment value: 0.8 separation value: 0.12 cohesion value: 0.8

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particle number: 250 alignment value: 0.8 separation value: 1 cohesion value: 0.15

particle number: 500 alignment value: 2 separation value: 0.12 cohesion value: 0.15

particle number: 500 alignment value: 0.1 separation value: 0.12 cohesion value: 0.1

DIAGRAM

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 1 CODE Particle number of 700 and rangeOfVis of 20 is given as a fixed variable. The parameters of this code are: For (int I = 0; i<700; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(-10,10),Random(-10, 10), 0); The agents start from a central box and then spread over the whole simulation. The velocity is a high range between 10 and -10 which means the agent could continuously move in both directions. coh.scaleSelf(0.15); sep.scaleSelf(0.12); ali.scaleSelf(1); wan.scaleSelf(0.3);

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 2

TYPE 3

CODE

Particle number of 500 and rangeOfVis of 20 is given as a fixed variable.

Particle number of 300 and rangeOfVis of 20 is given as a fixed variable.

The parameters of this code are: For (int I = 0; i<500; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(10,10),Random(-10, 10), 0);

The parameters of this code are: For (int I = 0; i<300; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(10,10),Random(-10, 10), 0);

The agents start from a central box and then spread over the whole simulation. The velocity is a high range between 10 and -10 which means the agent could continuously move in both directions.

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coh.scaleSelf(0.15); sep.scaleSelf(0.5); ali.scaleSelf(0.8); wan.scaleSelf(0.3);

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coh.scaleSelf(0.8); sep.scaleSelf(0.12); ali.scaleSelf(0.8); wan.scaleSelf(0.3);

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28 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 29

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

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TYPE 5

CODE

Particle number of 250 and rangeOfVis of 20 is given as a fixed variable.

Particle number of 500 and rangeOfVis of 20 is given as a fixed variable.

The parameters of this code are: For (int I = 0; i<250; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(10,10),Random(-10, 10), 0);

The parameters of this code are: For (int I = 0; i<500; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(10,10),Random(-10, 10), 0);

The agents start from a central box and then spread over the whole simulation. The velocity is a high range between 10 and -10 which means the agent could continuously move in both directions.

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coh.scaleSelf(0.15); sep.scaleSelf(1); ali.scaleSelf(0.8); wan.scaleSelf(0.3);

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coh.scaleSelf(0.15); sep.scaleSelf(0.12); ali.scaleSelf(2); wan.scaleSelf(0.3);

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30 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 31

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 6 CODE Particle number of 500 and rangeOfVis of 20 is given as a fixed variable. The parameters of this code are: For (int I = 0; i<500; i++) { Vec3D p= new Vec3D(random(30,90), random(30,70), 0); Vec3D v= new Vec3D(random(-10,10),Random(-10, 10), 0); The agents start from a central box and then spread over the whole simulation. The velocity is a high range between 10 and -10 which means the agent could continuously move in both directions. coh.scaleSelf(0.1); sep.scaleSelf(0.12); ali.scaleSelf(0.1); wan.scaleSelf(0.3);

32 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

PATH FOLLOWING LOGIC The inputs are agent-based, meaning the column starts at certain coordination points and ultimately moves to end points (ie. targets) following specific paths. These paths can also be described as the desired velocity. The code guides the agents through so called steering to stay inside of the cylinder measurements. The agents are, as a response, attracted to the middle of the column. The Data Dam collects the agents with the network between adjacent points. After that, the velocity lines can become visible as well as the network lines. As soon as the multi-agent column is built up, the Variable Sweep makes the growing towers apparent. These multiple towers together create the column. The growing of the column happens in a bottom up manner.

TYPE 1

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Particle Path: 1 Particle Number: 400 Trail Size: 200 Rotation Trigger: 6

Particle Path: 2 Particle Number: 300 Trail Size: 200 Rotation Trigger: 8

Particle Path: 3 Particle Number: 400 Trail Size: 200 Rotation Trigger: 6

TYPE 4

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TYPE 6

Particle Path: 4 Particle Number: 200 Trail Size: 200 Rotation Trigger: 3

Particle Path: 5 Particle Number: 500 Trail Size: 200 Rotation Trigger: 4

Particle Path: 6 Particle Number: 400 Trail Size: 200 Rotation Trigger: 3

The input of the data guides the agents to go randomly to the top, but to be kept inside a radius of 20. The output is that the randomness is combined with the steering and the velocity.

DIAGRAMS

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 1

TYPE 2

CODE

400 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of 6.

300 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of 8.

Type two agents are influenced by the movement of Type one agents, with a range of vision of 200, and traverse the environment following the trails of Type one.

The agents eventually begin swarming around in clumps, without ever really setting down due to their increasing wander.

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if (type == 1){ coh.scaleSelf(0.3); sep.scaleSelf(0.4); wan.scaleSelf(0.2/(frameCount)); } if (type == 2{ sep.scaleSelf(0.5); tra.scaleSelf(0.7); }

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36 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

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CODE

400 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of 6.

200 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of 3.

Type two agents are influenced by the movement of Type one agents, with a range of vision of 200, and traverse the environment following the trails of Type one.

Type two agents are influenced by the movement of Type one agents, with a range of vision of 200, and traverse the environment following the trails of Type one. FRAME 18

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38 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 39

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 5

TYPE 6

CODE

500 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of 4.

400 agents are initialized from the bottom of the cylinder. Type one agent move in z-axis within the given environment of cylinder with rotation trigger of .

Type two agents are influenced by the movement of Type one agents, with a range of vision of 200, and traverse the environment following the trails of Type one.

Type two agents are influenced by the movement of Type one agents, with a range of vision of 200, and traverse the environment following the trails of Type one. FRAME 12

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40 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

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ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 41

CHAPTER 3: STIGMERGY

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

STIGMERGY 2D LOGIC

DIAGRAMS

Stigmergy is a communication method used in decentralized systems in which individuals communicate with each other by changing the surrounding environment. Stigmergy was first observed in social insects and then applied at artificial intelligence system. Ants exchange information by laying down pheromones (the trace) on their way back to the nest when they have found food, in this way they collectively develop a complex network of trails, finding the shortest path to a food source and connecting the nest in the most efficient way.

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When ants come out of the nest searching for food, they are stimulated by the pheromone to follow the trail towards the food source. The network of trails functions as a shared external memory for the ant colony.

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

STIGMERGY 3D LOGIC The goal of this assignment was to define and apply stigmergic environment on a box with a width and length of 20cm and height of 50cm. The Stigmergic environment is developed by applying vector and Forces on the 3-Axis. The agents respond to the environment by moving around on the box with the force on the 3-axis.Changing the variable such as the separation, cohesion and particle numbers could result in various forms of the design; but following the same concept, the Stigmergic Environment.

TYPE 1

Cohesion Magnitude: 5 Cohesion Range: 30 Separation Magnitude: 0.2 Separation Range: 20 Particle Number: 500

TYPE 4

Cohesion Magnitude: 6 Cohesion Range: 60 Separation Magnitude: 0.2 Separation Range: 20 Particle Number: 600

46 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

TYPE 2

TYPE 3

Cohesion Magnitude: 4 Cohesion Range: 30 Separation Magnitude: 0.2 Separation Range: 60 Particle Number: 400

Cohesion Magnitude: 2.5 Cohesion Range: 75 Separation Magnitude: 0.2 Separation Range: 20 Particle Number: 300

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TYPE 6

Cohesion Magnitude: 10 Cohesion Range: 30 Separation Magnitude: 0.2 Separation Range: 20 Particle Number: 400

Cohesion Magnitude: 2.5 Cohesion Range: 30 Separation Magnitude: 0.2 Separation Range: 20 Particle Number: 1500

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 47

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 1

TYPE 2

CODE

For a number of 500 agents, which starts at random positions of the box width and box height:

For a number of 400 agents, which starts at random positions of the box width and box height:

for (int i = 0; i<500; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

for (int i = 0; i<400; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

Vec3D v=new Vec3D(random(-4,4); random(-3.5, 3.5), 0);

coh.ScaleSelf(5); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<30) traScaleSelf(0.9);

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coh.ScaleSelf(4); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<30) traScaleSelf(0.9);

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In this code, which the agent identifies more that 30 neighbors in the range of vision it becomes more attracted to the traits of those agents and gives the following pattern.

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 3

TYPE 4

CODE

For a number of 300 agents, which starts at random positions of the box width and box height:

For a number of 600 agents, which starts at random positions of the box width and box height:

for (int i = 0; i<300; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

for (int i = 0; i<600; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

Vec3D v=new Vec3D(random(-4,4); random(-3.5, 3.5), 0);

coh.ScaleSelf(2.5); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<75) traScaleSelf(0.9);

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coh.ScaleSelf(6); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<60) traScaleSelf(0.9);

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Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

TYPE 5

TYPE 6

CODE

For a number of 400 agents, which starts at random positions of the box width and box height:

For a number of 1500 agents, which starts at random positions of the box width and box height:

for (int i = 0; i<400; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

for (int i = 0; i<1500; i++) { Vec3D p=0 Vec3D((random(boxWidth), random(boxHeight), 0);

Vec3D v=new Vec3D(random(-4,4); random(-3.5, 3.5), 0);

coh.ScaleSelf(10); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<30) traScaleSelf(0.9);

FRAME 2

FRAME 29

FRAME 49

FRAME 81

FRAME 111

FRAME 148

52 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

coh.ScaleSelf(2.5); sep.ScaleSelf(0.2); ali,ScaleSelf(0.2); wan.ScaleSelf(0.3); } if (neighborList.size()<30) traScaleSelf(0.9);

FRAME 5

FRAME 37

FRAME 55

FRAME 78

FRAME 100

FRAME 157

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 53

CHAPTER 4: MESH GENERATION

Workshop 2 - “200 Lines of Code and a Video” | 06.01.2021

MESH GENERATION LOGIC

CODE

The mesh generation simulation is based on the path following principle. The code directs the agents from start to end and through the specified path, and radius of rotation as well as distancing from the main core. Throughout the creation of the basic pattern that later on is transformed to mesh through visual scripting, the agents decide their own paths based on the behavioral attributes allocated to them by the code. Where multiple intersections of paths are visible, the mesh is the result of the agents responding to a certain situation during their movement from start to end. As well, as shown in the visuals, the mesh is made of interwoven patterns which depict the manner in which the agents where rotating around the axis of direction and weaving the geometry as the simulation runs.

200 agents are initialized at the base of each of the paths. The agents from a weaving behavior around the path directions while moving from start to end, while doing so the agents move in a rotation based on the trigger specified in the code and are projected from the main path therefore they remain within the limits of the parameters set while never coming in contact with the core. the trails from the waving curves that later transformed into the geometry

DIAGRAM

Initial.pos corerandom(-50:50); particle number:200 Weaving settings: if{ Rot.trigger(6.0); Rad. scale(20.0); Sep.scaleSelf(20); } Multipath tracking if { projection.rad(13.75); projection.Dis(15); } After the trails are generated visual scripting comes into play where the trails are transformed into geometries where the trails are deconstructed into vertices placed equidistantly along the trailDiv=500, and these data list are connected to form the nurbs curves that are later transformed into meshes and joined together to form the mesh shown in the visuals.

56 | ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang

ENCODED BEHAVIOUR - Cheolyoung Park, Jamil Al Bardawil, Jonathan Zisser, Pin-ju Wang | 57

THANK YOU

Instructor - Shajay Bhooshan Cheolyoung Park | Jamil Al Bardawil | Jonathan Zisser | Pin-ju Wang