Blue Oak Mountain Technologies, Inc.
Artificial Life Technology Architecture Design and Development - Technology Licensing

 

What if what you thought you knew about Reality, Causality, Life Processes, and Consciousness is mistaken?

 

Study our website and discover a whole new way to think with a firsthand perspective that may surprise you!

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Artificial Life Technology Architectures that are Fundamentally Different and New

Blue Oak is reinventing itself to focus our business on our patented Artificial Life (AL) technology, also known as “digital biology” to some researchers. What is digital biology?  

We are developing new architectures for Artificial Life (AL) as an on-going process, but we are using ideas that are very different from Artificial Intelligence (AI) designs in the state of the art. As you read these pages, you will discover that we think differently about both AL and AI, much differently than most others in these fields. And while our ideas do fit into the broad category of digital biology, you may find they are quite unlike anything else in that field because our focus is goal-directed biological behavior as a conditional system of proactive causal interaction between an organism and its environment, its specific habitat. A system that is conditional in the sense that our simulated organism must proactively maintain its own future existence like a real organism does.

Our ideas may seem new or even strange to you. But study and think about them carefully, and we think you will find our thinking is part of a cohesive, wider system of ideas that has the potential to change AL in many positive ways. You may find our views differ from those of many others as follows:

Point 1) As explained on succeeding pages, we think of both biology and our simulations in terms of system architectures that consist of layered conceptual abstraction models that have proven their value over the years for developing many kinds of new systems. As explained below, system architectures are the result of design and development methods that are logically and causally connected to real world physical reality as their base and foundation. Each layer of a layered system model is its own causal context, and the layers only communicate with each other and the outside environment through standard interfaces in a manner analogous to how the Open Systems Interconnection (OSI) models works for computer network systems. The analogy is not perfect, but we believe it can be very useful to understand how both living and non-living causal systems interact internally and with each other. This approach has many benefits, as will be explained later. Both living and non-living systems are part of causal system architectures that are very different from each other in fundamental ways. But does that mean they cannot causally inter-operate? We think understanding both living and non-living systems in terms of their system architectures and what would be required for their system architecture integration can be very helpful in the field of AL. The issue of the causal interaction of causally incompatible mechanistic systems was solved a long time ago. Could applying similar methods work to better explain how living systems causally operate too? What is the OSI model?

Point 2) We think of life processes as primarily biological, not mechanistic. This is certainly the case above the molecular organic chemistry level of action that animates organisms. We think that the details of how organisms actually work can be more easily explained and understood when the life processes of an organism are described with a layered system archictecture model like the OSI model, modified to include goal-directed action. Such layered models are very useful to identify all kinds of different causal system interactions and their relationships to any desired level of detail. More biological ideas must be included in AL for life simulation systems to more accurately mimic organisms than commonly is in the state of the art. Biology, as it applies to the lives of organisms is the study of goal-directed, proactively relational processes that are a constant part of all living action. Each organism is constantly and inseparably related to its environment at every level in a goal-directed manner. This and many other facts about living organisms can be expressed in a system architecture model to whatever level of detail is required to fully understand them to map out the identity of all aspects an organism. When expressed this way, it is easy to see that there are many, many relationships of various kinds involved in all the interactions of an organism, both internal to the organism and external in the environment or habatat outside the physical organism. And these relationships are unique to every habitat, the identity of which is the ultimate cause of the existence of every organism in the first place. Focusing on the causal systemic functions of an organism alone, without constantly including its constant relational connection of environmental interaction, is an ineffective strategy. This approach is not effective because doing so implicitly ignores the inherently goal-directed relational nature of life processes. The internal identity and causal processes of the organism become the focus, and their environmental causes and constant interactions tend to be forgotten or at least de-emphasized. So we spent many years studying a new way to think about life that provides better, reality connected conceptual models and a bigger and more mathematically precise picture about how organic system logic works in general, as well as the crucial aspects of how organisms relate to their environments. Yes, system archictecture models were originally created for software and other kinds of mechanistic system design and development, sometimes called systems analysis and knowledge engineering. But over the years it was learned that people (users) and the choices they make are valid causal inputs to mechanistic systems as well, and need to be included for the designs so they work properly. People are now considered an integral part of many system architectures for business and other kinds of integrated systems, but they are not typically used to express to express goal-directed action as such as its own causal system architecture. We are simply including goal-directed relationships in AL a new way to explain how organisms are related to their environments, to show how their internal processes work to make the relational nature of organisms possible, and to show how this whole architecture works by means of new kinds of causation. In fact, software engineering design and development itself is really a method for identifying and/or inventing new kinds of causal processes, predicting how they will operate when executed in the real world, monitoring their operation, and validating that they perform within some set of specifications or perfomance envelope. Our view is that these methods could be called "causality engineering," and since organisms are causal too, many software engineering methods should be very useful for describing and understanding their causal operation, both internally and in relation to their environments. One more point about layered system architecture models: They cannot be arbitrary or "floating abstractions." If they are, they simply do not work properly. If a system architecture model contains arbitrary formulations or has other errors, the software and other systems produced with them simply will simply not work properly or at all when executed. The test of the validity of the causal processes in a new system architecture design is if it actually works properly in the real world according to its design specifications. It either does or it does not.

Point 3) Biology may be based on the mechanisms of bio-chemistry, but the processes of organisms are proactive in relation to their environment. Proaction" is a form of goal-directed action that is causally different from mechanistic "reaction." After each proaction, the organism reacts in complex ways according to the identity of its internal causal processes to register changes in its environment and compare them to its survival needs. Then the organism proactively does something to fulfill its needs using self-generated energy to do so according to some set of implicit or explicit values its life requires to exist. Organic systems internal to an organism are all specific, limited, quantitative processes that operate in their own specific contexts. And if the organism survives, then it gets to act again to cause its own future survival --- indefinitely (either until if fails to survive a proaction or it simply wears out). There is a system architecture and logic to this cycle that is not causally the same as the mechanistic system logic of computer systems, but rather a form of active system logic we call "teleologic," or goal-directed logic. A relational, quantitative, goal-directed logical system is just as valid as a mechanistic logical system because it operates by the same Law of Identity and Law of Causality as mechanical logic does, but is simply different in the way it works. If you keep reading, you will find out why that is the case and how teleologic systems work to keep life processes in existence.

Point 4) We think differently about causality too. Why is this important? The answer is that there are many apparent contradictions between both biologically automatic and free-willed goal-directed action of organisms and the way we think about mechanistic system logic. The commonly accepted view of causality does not explain organisms very well. The ideas we have about living actions seem to contradict many state of the art ideas such as mechanical determinism, or the so-called "random chance" that is assumed to govern both mechanical and living processes. Neither accounts for the differences between living and mechanical processes as active systems. We have concluded that these apparent contradictions are the result of a faulty concept of causality that most people have learned and few people question. After investigating the logic of goal-directed action we now seriously question the traditional idea of causality as it is usually applied to mechanical and life processes alike of simply two events in a sequence, like billiard balls colliding. With the new causal concept we use any apparent contradictions between biology and mechanism can be resolved, as is explained in our work and references that follow on the pages of this site. We think this new concept of causality if used in conjunction with layered system architecture models will lead to more progress in AL systems design. Our view is that causality is not merely an event-action, "billiard ball" type process. The world or environment consists of entities and other existents (including organisms), each with a specific set of properties in specific amounts. And all these things have specific, quantitative relationships to each other that are reflected in an organisms many processes. There is more to these processes than a simple succession of events. They are not simply sequenced events occurring one after the other even with mechanical cause and effect. But rather, implicit in all process steps is all the information relating to two things interacting (including quantities) is part of the overall context of causality for each cause and effect instance that occurs, and these relations occur at many levels of complexity. This view is our concept of causality, what we call identity-interaction causality, which is an inherently quantitative, relational process that much better explains the causal interactions of both non-living and living things in our opinion. This new concept better explains causality because it includes the full context of how things relate and interact, and that context can be made explicit to whatever level of detail is necessary. Each instance of cause and effect becomes a quantitative transaction that occurs in a specific causal context, not merely two events in a simple temporal sequence of one after the other.

With identity-interaction causality, what a thing is determines what it can do according to the following observation based inductive generalization: Identity determines action capacity in every causal action context. By using that principle in our AL system designs, we have been able to find much more effective ways to simulate life processes than the state of the art.

Even life processes like sensory perceptual and conceptual consciousness can be more clearly understood with identity-interaction causality as a natural, biological,  causal process of organisms that produces quantitative content for the purpose of acting in relation to their environment in order to survive. We believe that to understand an organism, and especially a conscious organism, the context of its environment or habitat must always be considered. In a similar manner, if the context of biology is dropped when one is trying to understand consciousness, then there is almost no limit to the questionable conclusions that people can draw. While you read the following article, ask yourself how it differs from the approach to thinking about this topic we have just described. Ask yourself what conclusions might result from framing a thinking approach that starts with firsthand observation, uses identity-interaction causality, and includes the biology of the conscious organism as the main context: Check out this article about Panpsychism.

 

Our subsequent pages explain how the concept of identity-interaction causality can be used to better explain the relational nature of biological processes in general, and how this new understanding can be used to improve AL simulation system designs, especially if layered system architecture concepts are used with a biological framework as causality schematics. We hope you enjoy reading our pages.

If you find these ideas interesting, feel free to read more, including our book, white papers and the references we suggest. These documents will introduce you to a whole new way to think about AL and how to design new AL simulation systems with much wider life-like capabilities.

If you find our ideas objectionable or simply uncomfortable because the preceding paragraphs run counter to many common belief systems or other ideas you may have adopted from your culture, just below is a link to a book containing new way to think about both causality and the human ability to make choices. We are interested in readers who are willing to question their implicit beliefs. Are you one of them? Here is an opportunity to become one if you want to. You have the capacity of choice. Use it and learn!

Link to: The Illusion of Determinism

 

Technology Licenses

Our technology architectures are patented and must be licensed to users. We will offer licenses to those who want to utilize our technology architectures for AL projects of their own. But to do so requires that you grasp many new ideas first. For those interested, we suggest you read on to learn what you need to know, then email us your questions about how to move forward.

 About  Us

Learn about our company.

 Technology Architecture Details

Learn more about our views on digital biology and our Artificial Life simulation technology architectures, how they work, their benefits, and how our patented technologies can be used to create practical solutions.

 

 


 

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