About Organic Complex Systems
Organic Complex Systems (OCS) is a theory of living and lifelike systems. OCS seeks to identify essential properties and behavior that entities must exhibit in order be called "lifelike", or "alive.” It further intends to provide a mathematical theory to formally describe such systems.
OCS goes under the covers of biological systems in an attempt to discern salient characteristics that are deemed essential by this theory for embodying biological organisms with their lifelike qualities. It then asks the question "Are there any systems other than biological organisms that exhibit these same characteristics?" OCS answers this question in the affirmative, and then sets about articulating a general theory of living and lifelike systems.
The approach of OCS to the issue of "What is lifelike?" is to identify a reasonable set of essential systemic properties and behaviors of biological systems. OCS then defines any entity - biological or not - to be "lifelike" as long as it exhibits these properties and behaviors. Thus, OCS seeks a general theory of the living that includes, but goes beyond, traditional biology.
Traditional biology takes a different approach. It studies biological organisms with an eye toward "what are living entities made of?" Biology has shown that the answer to that question is essentially "carbon chemistry." Biology has gone on to show that life has evolved through natural selection from existing life forms. Of course, this has been a very fruitful endeavor resulting in the marvels of modern biology.
But the biology approach of defining "life" by what it is made of is often too narrow for 21st century purposes - where synthetic biologists are assembling new "life forms" from biochemical parts; where systems engineers are trying to build "artificial life" from computer software abstractions; and where NASA expects to encounter non-carbon-based "life forms" in its interplanetary exploits.
OCS provides an alternative, systems-theoretic view of “the lifelike": a set of seven systemic properties, or behaviors, that imbue any entity with the right to be called "lifelike" if that entity exhibits all seven of those properties - whether or not it is biological. (Other sets of such properties could also prescribe reasonable foundations for alternative theories of the living. But the particular set selected by OCS defines a style of living that befits the perspective of its author, and for which ample examples abound in nature and in culture.)
This list of seven systemic properties, then, defines a class of systems, all of which qualify - according to this theory - to being deemed as “lifelike” by the theory. This class is then referred to as “organic complex systems”. OCS is thus a theory of this class of systems. The phrase “organic complex systems”, then, serves dual purposes: to name the theory itself, and to name the class of systems that the theory describes.
And OCS goes further. It provides a mathematical foundation that formally embodies these seven systemic properties. Its mathematical constructs are used to design, model, build and predict the behavior and organization of the entities of this class. Thus, OCS provides fresh insight into what it could mean to be "alive."
The Issue
Recent decades have seen exponential advances along many of the frontiers in biology, some of which challenge long-held beliefs about the fundamental nature of biological systems. Active research now addresses such issues as:
- Renewed investigation into the origin(s) of life
- Life in extreme environments here on Earth
- The possibilities of life forms in outer space or on other planets
- Whether or not non-carbon-based molecules could be the basis for new life forms
- Possible artificial life in the form of computational software
- Emergent, self-organizing mathematical models and “organisms”
These thrusts return us once again to the question of “what is life?” and whether we understand its fundamentals well enough to model known biological phenomena and to predict as-yet-unknown biological systems and behaviors.
What is needed is a systems-oriented theory of living and lifelike systems that provides a view of "aliveness" based upon systemic properties and behavior, rather than on a particular predefined constitution. OCS provides such a theory.
Life Beyond Biology
OCS is a stochastic dynamical systems theory of living and lifelike organization that lies beyond traditional biological understanding. Such systems may include artificially-engineered lifelike systems, non-carbon-based extra-terrestrial organisms, synthetic biological systems, autonomic software systems and others that are not yet identified or defined.
OCS is based on seven concepts that define a class of dynamical systems that is considered to be lifelike. This class includes, but is not limited to, biological organisms. These concepts - named organization, emergence, compositeness, reorganization, autocoorganization, uncertainty and persistence - are organizing principles of living and lifelike systems. OCS presents both a colloquial and a mathematical articulation of these concepts and principles. Thus, OCS provides a new systems-oriented perspective of what it means to be "alive."
An Alternative to Chaos Theory
OCS requires a mathematical underpinning through which it can formally articulate its principles of organization. Nonlinear dynamics (chaos theory) seems an obvious candidate for this role, since it formally articulates some of the seven concepts of OCS.
Unfortunately, nonlinear dynamics is strictly deterministic - a fact not always understood, though declared by its adherents. Chaos theory studies dynamical systems that are “sensitive to initial conditions”. While such systems may produce unexpected outcomes, they are nevertheless deterministic, and therefore completely predictable - contrary to popular understanding. Consequently, nonlinear dynamics cannot account for the crucial role that uncertainty, randomness and probability play in living and lifelike systems. Thus chaos theory cannot adequately serve as a mathematical foundation of OCS. It appears that complexity science must develop a new kind of complexity theory to accommodate these requirements.
And so we have developed the theory of Organodynamics to provide the mathematical underpinnings of OCS. Organodynamics is best understood as a stochastic (probabilistic) dynamical complex adaptive systems theory. As such, it provides a probabilistic alternative to nonlinear dynamics and chaos.
The most significant distinction between Organodynamics and nonlinear dynamics is found in their respective mathematical foundations. Nonlinear dynamics achieves complexity through the use of nonlinear functions and equations - differential, integral and algebraic. This being so, its mathematics are strictly deterministic. But Organodynamics achieves complexity through a mathematical foundation that integrates uncertainty and certainty, or randomness and determinism, based on probability theory and its offshoots, stochastic processes and information theory.
Components of the OCS Program
The OCS research program includes four interrelated activities:
- The conceptual theory is the natural language articulation of a collection of seven organizing principles that must be exhibited by an entity to qualify as an "organic complex system."
- The formal theory, named Organodynamics, is a mathematical embodiment of the conceptual theory. It is based on the mathematics of probability and information theories. Organodynamics establishes the necessary rigor and detail to be able to define the modeling paradigm and the software library.
- The modeling paradigm is a toolset of building blocks for constructing mathematical models of organic complex systems without having to refer directly to the mathematics of Organodynamics. The toolset works by using the analogy of a directed graph from graph theory as a simplified representation of the mathematical constructs of Organodynamics.
- The in silica implementation is a software library that implements the OCS modeling paradigm. Its purpose is to significantly increase the speed of designing and implementing OCS models.