KNOWLEDGE POOL
AEco functions by creating a virtual ecosystem in which individuals exist and interact with each other. Each of the individuals can access and combine its own personal knowledge with family knowledge, and ancestral knowledge. When an individual dies, their knowledge becomes part of the ancestry. If an individual gains enough energy, it reproduces and passes on its knowledge to its offspring. AURA
The AURA, or leader, emerges from the group when an offspring is predisposed to do so. The Aura has the responsibility to behave cooperatively with the other individuals. If its behaviours are deemed uncooperative, it gets demoted, its knowledge becomes part of the ancestry, and a new Aura emerges from the group.
ANCESTRY
As individuals die, their knowledge becomes part of the ancestry, which is recorded in two JSON files. The first file is for the individuals, and the second file is for the AURAs. When the ancestral knowledge becomes too large, the earliest ancestors are re-amalgamated together, creating a single average value. This prevents the ancestry from becoming too large, while allowing a form of perpetual memory within the system. This type of knowledge is never erased even when the system shuts down.
INTERPRETATION MODES
Interpretation modes are used to determine how living individuals interpret the ancestral knowledge. There are four modes of interpretation:
* Average: it analyses the whole ancestry and creates an average knowledge
* Highest: it only takes the newest ancestor
* Lowest: it only takes the oldest ancestor
* Random: it picks an ancestor at random
The interpretation mode is assigned to each individual at birth and it can be passed down to offsprings.
TASK COMPLETION
The ultimate goal of AEco is to complete a task that requires a collective solution. As individuals move and exchange knowledge, new emergent behaviours are generated, leading to a collective solution over time. The AURAs play a crucial role in leading the system towards this collective solution.
EMERGENT MYTHOLOGIES WITHIN THE SYSTEM
Some of the values within the JSON files have been plotted and analysed, and from these studies have emerged some behaviours which are comparable to localised mythologies between sets of individuals. For example, especially cooperative AURAs tend to be remembered by individuals even after several generations, also every so often some extremely rare but supportive AURA is prophesied. There are also rare and mysterious AURAs that are very rare to come across. These individuals possess exceptional leading abilities, and their appearance is often prophesized for generations. These AURAs are believed to hold the power to lead the entire system towards a collective solution and unlock new emergent behaviours. These emergent mythologies continue to evolve and adapt, adding an extra layer of transcendence to the ecosystem.
/* ------------------------* * * * * * * * * * * * */ ------------------------e 888~~ ,d88~~\ ~~~888~~~ d8b 888___ e88~~\ e88~-_ 8888 888 Y88b / /Y88b 888 d888 d888 i `Y88b 888 Y88b/ / Y88b 888 8888 8888 | `Y88b, 888 Y88b /____Y88b 888 Y888 Y888 ‘ 8888 888 /Y88b / Y88b 888___ ‘88__ / ‘88_-~ \__88P’ 888 / Y88b ########## # # # ###### # ### ########## # # # # ## ## # # ########## ## # ## # # ## # # # # # # ## # # ## # ### # # # # ## ## ## # ### # # # # ## ### ## # “
STx TASK
STx can host up to 100 individuals, the pool size is ditacted by the AURAs success in leading the group. The more generations an AURA can manage to lead, the more individuals are allowed in the system.
STx goal is to decode a message embedded within its ancestry. The message can only be decoded in its entirety if the population is at full capacity. Each individual can only decode one word, and whenever it dies, the word gets erased.
The message is the following:
* But in this unstable, unbalanced spirit,
* ideas crowd on one another, and escape,
* and give place to others, while those that
* disappear still leave their shadow brooding
* over those that succeed.
* So here on screen, across a slant of light
* that parts the air within the sheltering shade
* man’s arts and crafts contrive,
* our mortal sight observes bright particles
* of matter ranging up, down, aslant, darting
* or eddying; longer and shorter;
* but forever changing.
/*
------------------------*
*
* */ -------------------------
PHASES
AEco is designed for collective task completion, with the ability to adapt and generate new behaviours over time. The following phases outline its dyanamics:
A] Initialization
To start using AEco, the first step is to initialize the virtual ecosystem. This involves setting up the individuals and their initial states, including their energy levels, knowledge levels, and interpretation modes. The first AURA is also initialized, and its initial state is set.
B] Movement and Energy
Once the individuals are initialized, they begin to move based on the AURA’s movements. Each movement costs energy, and individuals can gain energy by getting close to the AURA. The movement is divided into several bands, each with different energy ratios. Depending on which band the individual moves to, they will lose less or more energy. Energy levels are important, as they determine whether an individual can reproduce or not.
C] Knowledge Exchange
As individuals move and gain energy, they also exchange knowledge with each other.
/*
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/*
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/*
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This knowledge is based on a mix of personal knowledge, knowledge passed down from its family, and ancestral knowledge. Personal knowledge is the record of all successful movements that the current individual has made, while familiar knowledge is passed down from the parent directly. Ancestral knowledge comes from ancestry (the dead part of the algorithm) and is never erased.
Individuals exchange personal, family, and ancestral knowledge.
Knowledge Exchange
Living individuals interpret the ancestral landscape using interpretation modes. Dead
Interpretation Modes
Ancestral Landscape
Phases
individuals' knowledge
recorded in
files and becomes part of the ancestral landscape.
is
JSON
Individuals move based on the AURA's movements and gain/lose energy based on band position.
Initialize the virtual ecosystem by setting up individuals and their initial states
Initialization Start Movement and Energy Task Completion End
Individuals work together to complete a task requiring a collective solution.
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AEco/AEco.STx, AEco.5o, AEco.16o.1i are ecosystemic models developed by Pietro Bardini.
