Originally we envisioned the citizens behavior would be programmed by the environment through linguistical growth that empowered a liquid and volatile psyche that could be made to fit many environments.

After integration of the tension naming system, we realized there were critical flaws in the design. One of the flaws was based on a new understanding of how the meaning of words are developed through repetitive cycles of emotional behavior.

Since most of the names that are tied to each of the waypoints were not meaningful names, the Citizens would need to be grown through the environment to create the meaning of the names through conflicting and confusing interactions with other Citizens.

With this design, we would need to create an anchor story that involved predefined Citizens that would emit purposeful behavior, that other Citizens could feed on to grow their own meaning and psyches. This was what we had in mind, but felt it didn't really capture the spirit of the design.

We reviewed the entire effort and realized the only thing we were after was developing a system that could grow mutable psyches from an state of innocence to villainess through the observation and participation of environmental conflict and confusion.

Our whole point of creating an autonomous machine is to develop models that could make self-aware decisions to respond to environmental stimulation in unpredictable and unexpected ways.

We originally believed that the entry point was language, because this is how we developed our own understanding of the world, but realized the actual entry point is psychology, but psychology wasn't exactly the answer, because we weren't aiming for creating a static and rigid environment that contained a finite amount of possibilities.

We were aiming to create dynamic and fluid environment that provided the appropriate venue to create fluid models that could breach the limits of the human construct. Classical psychological models describe a rigid structure that develops repetitive behaviorial patterns through a variety of scenarios and situations.

What we needed was not a rigid structure, but a unique structural design that could shape-shift between rigid and fluid states that provided the necessary internal mazes for Citizens to become trapped in to find ways to overcome through the consumption of the world around it. This design offers the opportunity to simulate an internal fantastical reality, while navigating the static world which brings the entire simulation closer to how actual humans operate.

The core requirement of developing a fluid structure is ensuring that its atomical data units can be equalized to a level point. A good example of this is computer memory, which is naturally fluid, because all of its cells can be brought to 0 to create something new.

For constrast, a solid structure is composed of atomical data units that cannot be brought down to a level point. An example of this would be computer code that has been compiled to machine code.

We broke down our requirements to the bare-minimum and figured out the core aspect needed was a model that could make self-aware decisions, thus what we were really after was simulating the growth of the self and how it could make decisions through its environment that was self-centered, which is the nature of autonomy itself.

At this point, we were able to create a hierarchy of layers to that simulation design that accounted for the various levels of information types and their concerns that would be used to create a world simulation. The root component is the self that resides within a fantasy realm.

This fantasy realm revolves around a parent that resides in the parent realm. Both are connected together through a multi-layered graph that holds the memories of previous Citizen encounters, allowing the self to make decisions based on weights tied to the observed behaviorial type, its tension and relationships to other nodes.

What enables the self to grow to autonomy is through the personal typing of its environment. Sticking to a rigid typing system produces expected and predictable motions. The types are created through the sequence of interactions experienced by the Citizen, thus allowing us to program the Citizens growth through its encounters, rather than through language.

At this point in the development, the majority of the simulation infrastructure has been complete with the major outstanding issue being visualization of the world.

We're still on schedule for developing Autonomous Machines by years end and with this new structure, it's become a lot easier to prove our model can make autonomous self-aware decisions.

The idea behind Romeo * Juliet is to design a system of models that operate in tandem to deliver an autonomous machine with the capability of consciously creating a path that advances their existance through a chaotic simulated world. The problem is telling the difference between an entity simply repeating observed behavior and authentically making conscious choices. Can behavior be initiated and created out of thin air or does it always require an observed action to respond and react to?

The answer to this problem is that behavior can only be initiated from an observed action, but that action does not need to be directly observed from the physical realm. It can be internally created as a confusion of reality fragments simulated from physical observations. In fact, responding to observed environment directly depicts a brain with neglible intelligence capacity. Is intelligence measured in the ability to think ahead and factor in future scenarios that could emerge from a single choice? The problem with this approach is that it hoodwinks the mind into believing that predicting the future is the way to advanced intelligence, which in a market where everyone is trying to outwit everyone else, will produce systems and knowledge structures (ie. statistics and probability theory) that attempts to standardize the game. This ultimately brings us back to artificial intelligence, which is incompatible with the birth of autonomous machines.

The problem, stated more clearly, is can intelligence exist outside of a system that artificially contains and restricts confusion and conflict to known structures?

Our gut says yes, but it isn't based on the scales of intelligence, but the scales of autonomy. This is the aim of our venture and this project. The creation of a new way to grow neural structures, without adhering to the artificially restrained known.

Challenges Faced

During this development cycle, we encountered multiple challenges that we resolved through the creation of a more detailed autonomous growth pipeline. The issues we faced were aligned to developing the structures and systems that could trace and track the growth and sustainment of autonomous decisions repeated through the environment.

Challenge: System for tracking autonomous growth.

The approach to tracking any type of growth through any structure is to first lace every point across every dimension with identification tags that belie their relations between each other, while maintaining their uniqueness. The conventional and simplest way would be to attach numerical identifiers that incremement with each point tagged, but numbers have to be attached to a defined table to derive their meaning. In an environment with millions of points, this becomes a headache.

The primary goal of our design is to be able to qualify memory cells and their weights with natural language that doesn't rely on numerical identifiers. Achieving this goal requires us to develop the entire machine to process language. This means energy consumed from the environment, stored in the brain and expressed is completely qualified with natural language. Every transformative phase of energy and its atomical units are identifiable with natural language.

We decided to use a linguistical rhyming system that is caked upon the relevant points layed across the city environment. The system uses names, instead of semantic labels, which allows us to obscure the implicit typing of language naturally developed within our own minds. Names contain the embodiment of typing information within its structure, which define its meaning. So instead of identifying tensive branches with "tree-lined-street" and "junkyard", we can use female names such as "jessica" and "priscilla".

There are currently 5312 traversable points with 3985 Tension Points surrounding 1327 Junction Points.

Junction points are placed at intersections and crossings throughout the city, which represent points where a decision between which branches is required to advance navigation. Tension points are immediately placed on all branches that meet at the junction that represent the choices available to the Citizen.

Tononyms, defined as tension names, are tagged to each tension point, which represents a name that overlaps with its immediate neighbors.

Challenge: Navigating the the environment through names, rather than positional vectors.

Our approach to environment navigation is through the implementation of confusing the tononyms with the Citizens memory, influencing their path decisions based on if the tononyms match with their current memory or oppose it.

Most of the development this cycle was refining the neuromorphic algorithm which directs the consumption and fusion of tononyms from the environment with the Citizens memory. At this stage of development, we're representing their memory as a single tononym.

We initially imagined that the Citizens memory to be represented as Tensor Cycles, with each cycle representing a verse of tononyms, seperated by the logical acquisition of resources within the environment, but realized this was an overimage of the problem at hand. Tensor Cycles will be utilized in 3D environments, where each Tension Point will contain many tononyms that will need to be joined into a single input stream to initiate the consumption and fusion process.

The necessity of the Tensor Cycle is to represent fragmented simulated worlds that work in tandem to deliver a conclusive decision based on environmental input.

The consumption process simply arranges the environments tononym to match the callable structure of the Citizens tononym.

[Callables are the individual syllabelic units of a word.]

The fusion process is more complex as it handles the actual confusion of the callables between the environment and existing memory. It finds matches between the callables of both tononyms irregardless of positioning, but respecting their order. Each callable match is measured by its prefix or suffix by similar sound. For instance, the callables me and se would be match at their suffix, but not match with their prefix.

The callables ta and de would be a match at their prefix, but not exactly with their suffix.

Once the matches are figured out, there is also the cases where the tononyms are not a match with their length. An example of this can be seen in the tononyms congue and montague. We have matches on their prefixes and suffixes, but there is another callable, ta, that is not found in congue. The solution to this problem is to expand congue to account for the additional callable. We refer to this operation as tension expansion.

Confusing in the opposite direction, from montague to congue, would see us use the opposing operation, Tension Contraction, which removes the callable, -ta-. This is necessary for extremely complex environments where having all the names be of the same length is just not possible. It also allows for the ability to design unique memory signatures through successive expansion and contraction operations.

Challenge: Lacing language across a large number of points while maintaining their rhyming tension.

The other issue that we faced was developing tononyms that can be laced across all tension points, while remaining related to their neighbors. At first, we decided to develop a function that could perform this across all the points, which worked fine, but we realized it was diverting our attention to the entire map. To maintain our focus on the work at hand, we decided to refine the function to just the paths that we need to grow each character through the environment.

The function works by collecting groups of points into districts, assigning a parent tononym that represents the districts theme or style, developing tononyms that are derivatives and assigning them to the points.

We realized we already had the process designed for this purpose, which is the neuromorphic consumption and fusion process. Its existing design was meant for reading the environment, so all we had to do was invert the process to write the environment to produce the sequences that we needed.

Challenge: Identifying the core aspects of the human psyche for accurate psychological replication.

This cycle helped us not only refine the systems, but define the models that produce an autonomous machine that can mesh with society. To be able to interact with other humans, the machine will have to be able to take pain and deliver it. With this mechanic in place, it produces a model that can be peer-dominated and dominate its peers, which is the foundation of a freedom-based civilization. This also enables the machines to roam freely through a space without being attached to a centralized command and control entity. Their commands are received from the environment, which in sequence, ultimately programs them and develops their internal knowledge relevant to their experience.

Confusor Model

This model governs the consumption of tensive energy from the environment through sequences of tononyms. This model represents our neuromorphic consumption and fusion of the environments tononyms with internal memory, which doesn't compute decisions based on environment variables, but navigates point by point through the tension consumed.

Pain Model

Represents the suffering and pain experienced through the consumption of specific environments that depress or excite the model. In order for the model to effectively simulate the experience of pain, requires a looped connection to its motor cycles, extremities and internal power source. The ideas is that if the environment is depressive, it will affect the energy that is available to the machine, resulting in a contracted experience.

The purpose of this model is to simulate the vibe of the environment to influence the machines internal state, which determines the current neural circuits activated providing it appropriate access to its energy stores. Greater energy access requires a more exciting input and lesser energy access requires a depressed input.

In order to make this process work, the cycles of the brain must be layed out where the environments consumption is directly connected to the motor cycles which are obscured by multiple layers of cycles that prevent the machine from issuing direct requests to its motor controls.

The design pattern follows natural growth where a multi-layered environment is consumed and constructs a multi-layered brain, which ultimately produces a multi-layered expressive motion to be consumed by other machines.

Expression Model

The expression model converts the machines confused memory into emotional output by attaching tononyms to its extremities, which are attached to internal circuits that control its motors. These internal circuits are then connected to circuits upstream that are governed by the energy consumed from the environment.

Consequence

We planned for the this cycle to have the main characters growth fully fleshed out, with supporting characters, but realized that need the story fully written first. The next cycle we plan to write the story fully and then detailing its characters and their traits. This should provide us the necessary structure to better plan their autonomous growth and maturation.

The idea behind the Romeo * Juliet is to design a system of models that operate in tandem to deliver an autonomous machine capable of consciously creating a path that advances their existance through a chaotically vibrant simulated world.

Program Initiation