Natural Systems & Biomimetics

Abstract

The basis of our study originates from the study of the African Matabele Ants and encompasses their governing behavior and social mechanics. Based on these principles we would program and stimulate their behavior as an agent based system. This would then be used to further the study of the factors influencing their behavior and vary parameters in experiments, to explore and observe changes in local parameters affecting global ones.

The process will consider stigmetry from the digital environment while encompassing movement behavior of the agent, while factoring in the individual agent decision in an indeterministic manner, will affect the overall outcome of the geometry.

Table Of Contents

INTRODUCTION……………………………………………….………………………………………….. 7 BEHAVIOR STUDY……………………………………………….…….……………………………….. 9 ALGORITHMIC ABSTRACTION …………………………………………………………..... 10

PSEUDOCODE……………………………………………….…….…………………………………….. 12 ITERATIONS……………………………………………….………………………………………………. 14 1: RANDOM MOVEMENT………………………………………………………….................. 14 2: SINGLE ATTRACTOR…………………………………………………………..................... 16 3: MULTIPLE ATTRACTOR …………………………………………………………………... 18 4: MULTIPLE STATES…………………………………………………………………………….. 20

ANALYSIS……………………………………………….…………………………………………………… 22 KARAMBA………………………………………………………….................. 22 CFD………………………………………………………….............................. 23 RADIATION …………………………………………………………………….. 23

PAVILION……………………………………………….……………………………………………………. 24 CONCLUSION……………………………………………….……………………………………………. 28

Introduction

The African Matabele Ants a specialized termite predator, solely raiding termites of the subfamily Macrotermitinae and exhibit unique behavior properties in response to their environmental stigmergy. The process of their movement, identifying the environmental situation and their response to the situation would be abstracted in our computational implementation.

Studying their unique attack behavior, we can observe that it is a response stimulus within their environment, but is only one type of stigmetry. The other elements of environmental response comprise of foraging, locating and engaging primarily define the rules of agent based movement. The computing logic defined by these primary rules are the general behavior of the agents in the environment and stigmetry that arise encompass these while transitioning.

The programed behavior for the agents will embody these principles of foraging, locating, engaging and attack in different sequential states, while leaving behind a geometric trail from the path sequence that emerged from engaging in the environment.

The attack behavior would be led by the first agent of many to locate a target of interest and would make traversing to the located target the main priority.

We will study the outcome of agents’ local interaction based on behavior rules that exist between them i.e. cohesion, separation and alignment. The patterns that arise from their interactions will attempt to rationalize the outcome of the global geometry that arise from following these three rules.

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Attack behavior displayed by Megaponera analis

Movement pattern of the Megaponera analis

Behavior Study The social insect we pursued to study is Megaponera analis is a strictly termitophagous ponerine ant species, found in sub-Saharan Africa from 25°S to 12°N that specializes in raiding termites of the subfamily Macrotermitinae at their foraging sites. The primary begins a scout ant locating and returning to its nest after having found an active termite foraging site and initiates a raid. It will recruit approximately 200 to 500 nestmates and lead them to the termites in a column-like march formation, which can be up to 50 m away from the nest.

Matabele ants live in colonies that can grow to sizes in excess of 20 million members. The ants are often seen on the march in search of food, especially once their supply has diminished. When the colony is on the march they move as one entity in a single column, with the larger soldier ants on the edge of the column providing protection for the smaller worker ants. While marching in their columns, smaller search parties break off in search of food and prey. Once food has been located, a pheromone is released to attract the rest of the column which quickly overwhelms it. The ants create a rattling or hissing noise as they move, but will do this especially when threatened.

The soldier ants possess formidable pincers which are easily able to puncture flesh or can be used as a defensive weapon. They are one of the world's largest ants reaching a size of 20 millimeters or more. Another defensive weapon, which is not often utilized, is the sting it possesses on its rear, which is sometimes used to dissuade any intruders or predators. The pincers are effectively utilized in the efficient dismemberment of their prey which includes grasshoppers, moths or even considerably larger prey such as mice and birds.

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ITERATION 1: Agents originate from the origin plane and move randomly within a bounding box. The first scenario the agents originate from one point and it is observed that this movement leads to the furthest branching.

The second scenario, has the agents originating randomly within 50 units surrounding the origin plane. Here it can be observed that the origin of branching and end branching are relatively similar in extent.

The third scenario, has agents dispersing randomly 100 units from the origin plane and the resulting branching extent is in between the first and second scenarios.

This iteration helps visualise how despite random movement is a embodied characteristic of the agents, it brings to light the importance of the starting conditions for the agents how they affect their overall outcome.

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Random Movement

ITERATION 1.1

Origin: XY Plane

Generated Geometry

Simplified Geometry

Iterations: 114 Agents: 9 Step Threshold: 200

ITERATION 1.2

Origin: 50 units radius

Generated Geometry

Simplified Geometry

Iterations: 114 Agents: 9 Step Threshold: 200

ITERATION 1.3

Origin: 100 units radius

Generated Geometry

Simplified Geometry

Iterations: 114 Agents: 9 Step Threshold: 200

ITERATION 2: Agents originate from the origin plane and move randomly, until being affected by the attractor point, within a bounding box. The first scenario the agents originate from one point and move randomly until they reach the attractor threshold, it is observed that this movement leads to the least branching before being affected by the attractor threshold.

The second scenario, has the agents originating randomly within 50 units surrounding the origin plane and then being affected by the attractor. Here the branching is most uniform and takes the longest to be effected upon by the attractor.

The third scenario, has agents dispersing randomly 100 units from the origin plane and the resulting branching shows it is quickest to be detected.

Unlike the previous iteration the first and last scenario had inverse results to the prior, where a point origin had the least branching and the last last scenario had the most branching.it can be noted that the introduction of an attractor significantly changed the results.

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Single Attractor

ITERATION 2.1

Origin: XY Plane

Generated Geometry

Simplified Geometry

Attractor: 1 Agents: 9 Attractor Threshold: 500

ITERATION 2.2

Origin: 50 units radius

Generated Geometry

Simplified Geometry

Attractor: 1 Agents: 9 Attractor Threshold: 500

ITERATION 2.3

Origin: 100 units radius

Generated Geometry

Simplified Geometry

Attractor: 1 Agents: 9 Attractor Threshold: 500

ITERATION 3: The three starting scenarios remain constant from the previous iterations.

The agents originating from a single point initially fall into the attraction field of one element. When transitioning from this point depending on the vector angle the agents are influenced by two attraction fields and undergo separation. The agents transition to the next attractor, while influenced by alignment.

It is observed in the second scenario, the agents separate from the beginning due to different starting positions and vectors, due to the influence of two attractor fields.

The path taken by the resulting geometries is observed the be the longest.

The third scenario, has agents taking the nearest attractor field and it is observed that the paths taken by most agents are similar to the first scenario but has variation with a few.

This iteration emphasises the proximity of the point to an attraction filed in relation to the current vector coordinates of the agent. It can also be observed that the attraction field is the driving factor for separation and alignment.

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Multiple Attractors

ITERATION 3.1

Origin: XY Plane

Generated Geometry

Simplified Geometry

Attractors: 6 Agents: 9 Attractor Threshold: 500

ITERATION 3.2

Origin: 50 units radius

Generated Geometry

Simplified Geometry

Attractors: 6 Agents: 9 Attractor Threshold: 500

ITERATION 3.3

Origin: 100 units radius

Generated Geometry

Simplified Geometry

Attractors: 6 Agents: 9 Attractor Threshold: 500

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Analysis ITERATION 1

Agents originate from xz plane and the wider field of spawning, giving the geometry the potential to be self standing.

ITERATION 2

Agents end at a point, giving the potential for the structure to be more resistant to rotation forces.

ITERATION 3

Agents originate from a wider plane and meet periodically at different attractor points, potentially making the structure stable and self standing.

RESULTANT GEOMETRY

STRUCTURAL ANALYSIS

WIND PRESSURE

RADIATION

Wind Force: 0.795 Kn/m2

Total Radiation: 4428.94 KWh m^2

Wind Force: 0.795 Kn/m2

Total Radiation: 4181.51 KWh m^2

Wind Force: 0.795 Kn/m2

Total Radiation: 3059.38 KWh m^2

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Radiation Analysis of Pavilion

Total Radiation: 534836.50 KWh m^2

Radiation Analysis of User Space

Total Radiation: 34836.50 KWh m^2

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