Brain

The Bibites is built upon one idea. That creatures can evolve to become better at what they do best; survive.

Their brain follows a custom algorithm loosely based on the rt-NEAT algorithm.

Bibites can evolve nodes and synapses in order to connect their Sensory Layer (input nodes) to their Behavior Layer (output nodes), resulting in complex behaviors which are dependent on the perceived state of their surroundings, as well as their internal state. List of Input and Output Neurons here.

At every frame of the simulation, their senses are recorded and their brain connections are processed in order to compute the activation level of every neuron of their Behavioral Layer. The behavioral layer is then used by the Bibite's system to produce its actual behavior.

A pdf linked in the simulation has some good information on the brains, starting on page 3.

Mutations[]

The structure, as well as the tuning of that brain structure, can change through mutations, and be subject to natural selection.

The mutation process is similar to the genetic mutation process in the sense that a gene (Brain mutation Chance) is used to randomly select how many (or any at all) mutation events occur when a new Bibite is birthed.

If a mutation event is triggered, we then have to determine what type of mutation the brain undergoes.

Possible brain mutations[]

Change Synapse Strength
Flip Synapse Strength
Toggle Synapse (disable/enable)
Add a new Synapse
Remove an existing Synapse
Change a Neuron's Activation Function
Adding of a new Neuron
Removing an existing Neuron

The probability of each happening is decided by related Simulation Settings:

Brain mutation settings[]

Synapse Mutation Chance
Neuron Mutation Chance
Synapse Change Chance
Synapse Flip Chance
Synapse Toggle Chance
Synapse Add Chance
Synapse Remove Chance
Neuron Change Chance
Neuron Add Chance
Neuron Remove Chance

It is important to note that Input and Output Neurons are locked and can't be subjected to mutation. Only Hidden Neurons can mutate and evolve. No restrictions are placed on synapses since they are not part of the fixed structures.

List of Neurons[]

Bibites can grow to have an infinite number of neurons and synapses (aside from energy limitations). However, they have a fixed (for now) number of Input neurons on their sensory layer and of output neurons in their behavioral layer. There is a more complete list here.

Input Neurons[]

Bibites have a fixed number of input neurons based around specific systems, which serves as senses for the bibites. They are updated each frames from the Bibite's internal state and it's environment.

Metabolic

EnergyRatio
Maturity
LifeRatio
Fullness (of its stomach)

Touchy feely

Speed
IsGrabbing
AttackedDamage
EggStored

Vision

BibiteCloseness
BibiteAngle
NBibites (number of visible bibites divided by 4)
RedBibite (red color gene of the closest bibite)
GreenBibite (green color gene of the closest bibite)
BlueBibite (blue color gene of the closest bibite)
PlantCloseness
PlantAngle
NPlants (Number of visible plant pellets divided by 4. It's unclear whether pellets the bibite is grabbing are included in this count.)
MeatCloseness
MeatAngle
NMeats (Number of visible meat pellets divided by 4. It's unclear whether pellets the bibite is grabbing are included in this count.)

Internal Clock

Tic (heartbeat)
Minute (internal chronometer)
TimeAlive (age)

Pheromones

PheroSense1 (red pheromone strength)
PheroSense2 (green pheromone strength)
PheroSense3 (blue pheromone strength)
Phero1Angle (red pheromone direction)
Phero2Angle (green pheromone direction)
Phero3Angle (blue pheromone direction)

Output Neurons[]

Bibites then have a fixed number of output neurons, which are used to update their behavior and interaction with their environment.

Accelerate
Rotate
Herding
EggProduction
Want2Lay
Want2Eat
Digestion
Grab
ClkReset (clock reset)
PhereOut1 (produce red pheromones)
PhereOut2 (produce green pheromones)
PhereOut3 (produce blue pheromones)
Want2Grow
Want2Heal
Want2Attack