1. Overview
2. Rules of Behavior
3. Rules of Evolution
4. Changing the Population Characteristics
5. Discussion
6. Download

Overview

The description below covers the GOOeFloys applet. The applet was heavily modified from the original written by Ariel Dolan aridolan@netvision.net.il

Rules of Behavior

GOOeFloys behavior is governed by two rules:

1. A rule specifying how to relate to one's own kind.
2. A rule specifying how to relate to strangers.

1. How to relate to one's own kind

• Prey - Identify two members of your flock that are near to you and try to stay close to them, but not too close
• Predator - Eschew your own in favor of moving toward prey

2. How to relate to strangers

• Prey - move away from predators
• Predator - move toward prey and attack

These are the Rewards and Penalties that influence fitness:

• Food is energy: Predators get food by biting prey resulting in an energy increase for predator, and decrease for prey. The metabolic inefficiency of the predator decreases net gain, so only a portion of the energy removed from prey goes to predator energy. Prey obtain food by moving more slowly, feeding on the microorganisms freely floating. If either predator or prey run out of energy, they die.
  
  • When prey dies, other, fitter prey breed on its carcass (or predator excrement) and come in from the left to join the flock
  • When a predator dies, prey breed on its carcass and come in from the left to join the flock
  • When the last predator dies, a new generation begins
  • At the start of a new generation, when predators are born, they can appear where the last died or come in from the right
  • It is necessary for lower lifeforms to first exist before breeding on remains of higher forms So if predators consume all prey, no more prey can spawn.
  • Obviously, prey get harder to kill as they get stronger
  • Predators only eat 'live' prey. When prey die, they decompose, vanish, and new prey are born.

• Moving: For both Predator and Prey moving results in an energy decrease. Prey moving slowly: Likelihood of energy increase is based on slower movement since prey eat freely floating microorganisms
  • Moving toward ones own kind: Cooperation increase
  • Prey bumping into prey: Safety increase
  • Predator bumping into predator: Cooperation decrease
  • Prey moving toward predator: Cooperation decrease

Changing the Population Characteristics

How to use the applet

• Modifying the static population
• Modifying the evolutionary factors

Modifying the static population

You can do the following:

• Insert a predator and watch how prey are chased and attacked. Notice how emergent flocking behavior of both predators and prey influence the predation process
• A barking sound means a predator has expired from energy drain
• A chirp sound means prey has expired from energy drain or being eaten
• Go to 'Edit Properties' and modify the environment, Click 'Update' to apply the new environment then (Optionally) Insert a predator"
• Follow individual GOOeFloys easily by displaying their ID numbers.
  The' Show Numbers/Show Shapes' button toggles between these display modes.
• Turn off (or on again) the sound effects (such as the bark or chirp of a dying GOOeFloy).
• Display information on all GOOeFloys by clicking the 'Show Info' button.
• Display a Help screen by the 'Show Help' button.
• Select a predefined population from the 'Predefined' screen.
• Reset everything to default by clicking the Restart button.

Modifying the evolutionary factors

You can do the following:

• Modify the fitness function. Go to 'Edit Properties' and assign Energy and Safety and Cooperation Weight Factors
  • If Energy weight is higher, GOOeFloys will evolve to be braver and possess higher speed and acceleration.
  • If Safety or Cooperation weight is higher, GOOeFloys will evolve to be more cautious and they will keep together
• Modify the Max Energy Dose or Max Safety Dose properties. This is another way to control evolution direction.
• Start with a diverse, random population: Click 'Scramble' several times. Each click will make the population more diverse. Click 'Start Evolution'
• Create a single new generation by clicking the Breed button. Each selection of 'Breed' will produce a new generation out of the current one.
• You can start the evolution process with various types of populations:
  • Start with a diverse, random population.
    Click 'Scramble' several times before selecting 'Start Evolution'. Each click will make the population more diverse.
  • Start with a homogeneous population.
    Use the default population, or one you defined by changing environmental parameters using 'Update' in the 'Edit Properties' screen.
  • Select a predefined evolutionary process from the Predefined screen.
• Limit the possible variation by clicking Limit Ranges button.
  This will ensure a more homogenous, less wild population.
• Examine the history of the evolution by looking in the History page in the Info screen.
• Stop the evolutionary process by clicking the Stop Evolution button.
  (This toggle button displays the label 'Stop Evolution' when evolution is on).

The simple behavioral rules produce interesting emergent behavior. When prey GOOeFloys are not disturbed by predators they stick more or less together and swim playfully in their home area. However, when a predator is introduced it will begin to chase and attack them. The emergent flocking behavior they exhibit seems by its inherent mechanics to disrupt the process of predation. The effect also takes place in nature; in schools of fish, herds of gazelle, and flocks of birds. One of the goals was to see if this behavior evolves over time. As you use the GOOeFloys Tank you can draw your own conclusions. The behavior is also present in the predators, although they make no attempt to move toward each other, their sharing of common goals and penalties for colliding with each other result in cooperative predation. Whether this too models the world of nature is left as a consideration.

• The lowest layer is the genotype:
  This is the actual chromosomal string on which the genes are encoded. The GOOeFloys genetic algorithm is based on a string of hexadecimal characters, where each group of 4 characters on the chromosome represents a specific trait. At this level, we have only character strings that mean nothing until they are interpreted.
• Here is an example of an encoded chromosome and each trait:
  
• The middle layer is the phenotype:
  Here the information encoded in the genes is translated into behavior, which can be seen in the real world; The Tank. For example, a specific character group in a specific location on the chromosome may define a specific GOOeFloy acceleration. The GOOeFloy movement we see on the screen is influenced by this value.
• The third layer is the evolutionary fitness:
  The fitness depends on the phenotypic properties, but not always in a direct and simple way. There are no genes for fitness. A GOOeFloy's fitness is maximized when both energy, safety, and cooperation are maximized. These requirements can be contradictory: To get energy by killing prey, an predator GOOeFloy must reach the prey before his brothers/competitors do, so he should be adventurous and independent. On the other hand, the cooperation element of the fitness is decreased when he is far from his neighbors. Moreover, even the energy gain is complex: Biting increases energy, but moving quickly reduces it, and being fast is required to get at the prey first. For prey, moving more slowly increases the chance of finding food, but increases the chance of being food, and moving quickly uses energy and reduces food intake.

So we have this chain:
Evolutionary selection is done by fitness, fitness depends on the phenotypic traits, and these are defined by the genetic string. The evolutionary operators themselves (reproduction, crossover and mutation), act on the chromosome string. The whole process is quite involved and indirect.

And the result can be unpredictable:
By modifying specific traits, we influence the emergent behavior in ways that are not always easy to predict. When the evolution mechanism throws its blind operators, there is almost nothing we can tell in advance. Therefore it is quite interesting to watch the behavior and evolution of GOOeFloys, even in this very simple system.

Download

For non-programmers: