Foreword

Advanced Systems Science in Retrospective & A General Systems Prospectus

by Hugh M. Lewis

Systems thinking and theory has been around for several decades now. General systems theory emerged in the 1920's in various countries and from a variety of disciplinary directions in the 1930's, essentially by scientists who felt a deep inadequacy with the conventional approach to scientific explanation and methodology at the time, but its development was postponed by and to some extent promoted by World War II. By the late 1940's and early 50's there was a clear convergence of theories from several directions that dealt with various aspects of this paradigm, including Norbert Wiener's popularization of cybernetics, Von Neuman's contribution to game theory, and the introduction of information theory by Shannon and Weaver. All of these advances must be seen as alternative perspectives on the same problem set of general systems theory. 

We owe a debt of gratitude especially to the seminal theorist and generalist Ludwig Von Bertalanffy for his formulation of the General Systems framework that has spawned new systems approaches in a dozen different scientific disciplines from physics through biology into the human science fields like psychology and even archaeology. It was he more than any other individual who first identified the general theory of systems as a central scientific problem set of concern to all areas of inquiry. Whether we are concerned with the analysis and description of the Eukaryote or prokaryotic cell as a system, or we are concerned with the analysis of global economies as a grand system of rational human behavior, or we are concerned with the most basic processes of the universe, the systems framework remains to provide us with the general sense of order and purpose that we can attribute to our knowledge and observations.

There are many different techniques and frameworks that fit somehow into the General Systems paradigm. We may mention a list that is growing, from early involvement in classical system theory, compartment theory, set and graph theory, net theory, cybernetics and control theory, information theory, theory of automata, game theory, decision theory, queuing theory, to heuristic modeling, systems engineering and analysis, to more recent involvement with chaos theory, complexity, non-linear dynamics and Mandelbrot equations. All of these areas provide insight into the General systems, and constitute a part of the larger framework in which this knowledge has been constructed.

I have of course put my own spin and polish on the problem of general systems, as I have sought to extend the basic concept somewhat in a number of different directions. I have found the original framework to be somewhat theory deficient, in terms especially of grand and what are known as middle level or intermediate theories. In stead of this deficiency, I've found a tendency towards an ideological and programmatic approach to natural problem sets within the general systems framework, without the realization that theory in different domains of knowledge is intrinsic to that knowledge and in many ways unique to that knowledge. 

I have found for instance, general systems theory entirely consonant with cosmological and unified field explanations at the level of fundamental physical reality, but this application is to be sought and found in the spirit of the principles of systems, and not in the letter or the terms which must remain intrinsic to the field of physics. In other words, a systems model must be found emanating from the pattern of relationships found to predominate in a field like physics, in terms and definitions most appropriate to this field, and cannot be superimposed in an arbitrary or abstract manner upon this pattern by General Systems theorists. On the other hand, systems models can provide heuristic insight and suggestive ideas for the reconceptualization of scientific fields, for rethinking old problem sets in new ways, and for allowing us to move beyond the paradigmatic blind-spots that hinder intellectual progress and development. Those who have talent in their knowledge domains for general problem solving must learn to seek and discover in their fields the patterns of relationship and implicit systems that are surely there to be discovered, in terms amenable one way to another to a systems model and approach. The same model that will work in one area of knowledge like physics will certainly not apply at all to another area in another disciplinary avenue, like biology or anthropology. There is no reason to think that  the theoretical models and constructs appropriate for a field like physics would be applicable at all to any other fields.

I would claim at this time the following general insights into systems theory:

1. Not all description of natural processes and patterns are characterizable in a meaningful manner by mathematical terms and relations. There is a sense of a finite limitation inherent to mathematical models that prevents us from applying such models in a more open and general manner to diverse kinds of data-sets. We may put this another way and state that though all physical event structures are mathematically describable and logically derivable, at least in theory, not all natural event structures are analytically reducible to purely or only physical systems, without the loss of emergent properties and synergistic pattern that is attributable to especially higher order systems.

2. Even for basic physical phenomena, natural event structures tend to be so complex that they quickly outstrip the capacity of mathematical language to parsimoniously describe.

3. Mathematical language, theory and formula are conceptually and symbolically derivative from an empirical substrate of meaning.

4. Conceptually formulated theories that are concise in their definition and reference may provide the most flexible and coherent language for many areas of science and natural systems thinking, as long as the conclusions are empirically or experimentally based through inductive observation and result in testable conclusions by a hypothetico-deductive methodology.

5. We face a central paradox of attempting to describe general systems that are considered basic and objective in terms that are ultimately rooted themselves in advanced symbolic and conceptual systems that are themselves derivable from the teleological development of natural systems. In short, we are bound within the very systems we are seeking to describe, and we are ourselves, including our conceptual systems, a by-product and a part of these systems. 

What is sought in grand theoretical terms of general systems science is a deep form of linguistic parsimony and precision of terms and definitive relations that has predictive and explanatory power across a wide range of variable phenomena.

I would say that implicitly at least, there has always been ample room in the sciences, at least in scientific knowledge itself, if not in the scientific community or in terms of its social articulation and application, for a comprehensive and comprehensible general systems perspective, just as there has always been room for synthesists and synthesizing activity to attempt to understand natural patterning of phenomena from a holistic and emergent-property standpoint. The proclivity to promote a certain analytical-cognitive style and approach to knowledge, pretty much across the sciences, may have been an unfortunate by-product of an entrenched and tradition-bound academic structure that has defined itself in terms of disciplinary and sub-disciplinary boundaries, as well as a certain premium placed upon the experimental, observational discovery of new, fact based knowledge, sometimes at any and all costs.

Lack of clear interdisciplinary communication, and I would claim, integration, has in the history of the development of general systems theory tended to hinder its progress and coming together as a unified field of inquiry. In the 1960's journals and societies developed from different directions with the aim of providing the context for such interdisciplinary communication and integration, and to some extent these efforts were partially successful in the forging of a coherent knowledge structure for general systems theory. I would claim though that disciplinary compartmentalization and especially academic-based hyper-specialization of knowledge expertise continues to undermine and interfere with the further development of a general systems framework. 

The problem of interdisciplinary integration must be seen as reaching beyond the context of cross-disciplinary communication that implies a cooperative sharing of ideas, knowledge and skills between different kinds of experts from different backgrounds, especially when united by common problems or objectives. It implies a fusion of knowledge across multiple boundaries in a manner that should result not so much in "cross-fertilization" of new ideas, but in the development of a totally new comprehensive perspective that is inherently multi-disciplinary in orientation.

Meta-systems is a concept not only of a system of systems, or of an attempt to deal with complex, heterogeneous systems that are composed of a hierarchy of subsystems, but also it implies, perhaps more importantly, an interdisciplinary framework for the reorganization and reconceptualization of knowledge, especially scientific knowledge, in a manner promoting interdisciplinary integration and the dissolution of knowledge boundaries that tend to interfere with such integration. What a meta-systems framework provides therefore is a new comprehensive paradigm for the unification of scientific knowledge across all disciplinary fields and sub-fields, in a manner that retains the integrity of each disciplinary sub-field, and yet provides a context for its integration with other sub-fields and disciplines.

A beginning to this integration is recognition of the innate and natural boundaries separating fundamentally different domains of knowledge. There is no sense in mixing apples and oranges in our formulations. The basis of this is the recognition of the natural hierarchy of meta-systems, and the nonequivalence of theoretical explanation or even of descriptive terminology from one level to another within this hierarchy of systems. We may adopt a physics of human symbolic behavior, but this is unlikely to yield productive results compared to the conventional physics of subatomic particles and fields. The problem of the hierarchical stratification of natural systems leads to the relative appropriateness of theoretical terms, definitions, and relationships we draw in relation to different domains of scientific knowledge. It becomes merely inappropriate, and probably irrelevant as well, to mix our scientific metaphors, so to speak, and to refer what is essentially anthropological or even biological phenomena to a physical level of analysis and explanation. Of course, hybrid, hyphenated (and I should say frequently "hyphenated") approaches at least attempt this all the time, but rarely to such approaches yield any great or significant insight into the fundamental problems of reality. Another way of putting this problem is to suggest that we are unlikely to find the answers we really want if we seek a primary explanation to the cause of the Great Depression in terms of a cycle of Sun Spots, El Nino events, or the variations of the Earth's magnetic poles. If a huge meteorite took out New York City and most of the East Coast, we would probably have slightly more to worry about in our history books than another Great Depression.

It may seem paradoxical to claim that the basis of integration is stratification and differentiation of sub-disciplines along natural boundaries, but we must realize that it is in the organization and interaction of these sub-disciplinary fields that we are to find the true integration proceeding, and not in terms of their isolation and further compartmentalization. It makes no sense either to put the physics department in the same wing and floor as the anthropology department, and expect that everyone in the building will become happy bedfellows. The interaction between anthropologist and physicist must therefore proceed at other levels, and in other ways, than merely in their behavioral articulation in department settings. It must proceed in a sharing of ideas and thoughts over a cup of coffee at a lounge table, unharried by administrative demands, within a systems framework that somehow transcends the disciplinary differences that exist between them. What of relevance might an anthropologist be capable of saying to a physicist, and vice versa, that would lend theoretical and methodological insight into their respective knowledge domains and associated problem sets?

At the root of this problem and dilemma confronting interdisciplinary integration is I believe, the natural organization of real problem sets and the non-reification of ideational or conceptual systems in relation to these problem sets. It should by now go without saying, as a somewhat trite Kuhnian type of cliche, that our problem sets and how they are defined theoretically and approached methodologically, both define and are defined by the dogmas and boundaries of our expert sub-fields. One of the key identifying features of any scientific sub-discipline is what can be considered a unique set of methods that are built and established around a unique set of problems in reality. The problem is not here, so much as it is in tackling a class of problem sets, what can be called meta-systemic problem sets, that by their complex nature transcend those boundaries established around traditional sub-disciplines. It is even a paradoxical issue to try to define what these problem sets are. The obvious example is the problem set centered around concerns for global ecology and global conservation, especially in relation to the further technological development of human civilization. No one sub-discipline can claim an exclusive handle or monopoly of methodology and theoretical insight into such a grand scale problem. 

The problem is real enough, and undeniable in its major outlines. But it is largely a problem that everyone is inheriting, but nobody seems to want to claim even partial ownership for. Therefore it becomes a problem that grows in proportion without antidote, prescription or solution being taken. But this problem is part of a deeper and more basic problem set that concerns human adaptation, social organization, evolution, and ecology, and that also concerns the role of geo-physical structures and processes in shaping and constraining the patterns that life takes upon the earth. This deeper level of the problem is not as taboo, and perhaps more available to sub-disciplinary definition and resolution, albeit in a limited and partial manner.

The advent of the computing age and the information revolution has made possible new patterns and capacities meta-systems integration in ways we can scarcely yet imagine. It is possible that we do not need to worry about building supercomputers powerful enough to solve essentially unsolvable differential equations, or extended mathematical problems of astronomic proportions, so much as we can learn eventually how to program and construct our computers in new languages that permit them to facilely express general insight into pattern or logically deduce new conclusions that is possible in nature and to model this patterning in ways that can be considered realistic and representatively reliable. I believe the computing power or capacity for this kind of meta-systems integration may be with us already, if only we knew how to bring it to effective realization in the construction and articulation of our working systems.

Beyond this issue of theoretical relevance and appropriateness, I would also make a claim for a general perspective of meta-systems science as an extension of a general systems theoretic framework, especially when natural systems involve inherent complexity arising not only from large numbers or large sets, but also especially from intrinsic heterogeneity of sets and components as well. Meta-systems I believe provides us with a framework for conceptualizing certain kinds of mixed problem sets, as systems collide and entangle with other systems in the real world, to determine what are ultimately underdetermined outcomes for a system. Meta-systems, to define simply, is not only a system of systems, but also a problem of how heterogeneous systems interact and interrelate.

It is reasonable to claim that all things in nature cohere into their own systems, ones that we call for the most part self-organizing, and these systems are all part of larger systems, and composed in turn of many smaller subsystems. We recognize no intrinsic upper or lower limits to this process of embedding and contextualization, or subordination and super-ordination of natural systems, though  we do deal with extrinsic observational limits to our capacity to perceive and therefore to know with any sense of first-hand certainty at levels and scales far removed from our own human-sized proportions. We identify super-ordinate patterns in terms of emergent properties that we can associate with hierarchical integration of function and holistic or organismic synergy, or rather the functioning of the entire system as a unique entity, which implies in itself systematic subordination as well. From these we adduce that all systems undergo developmental life or state-path trajectories and maintain a complex process of dynamic equilibrium of relationship and feedback with its environment. I make an assertion that human cultural systems are a natural outgrowth of more basic biological systems that have lead to the product of large brains, creative hands, and symbolic consciousness unique to humankind. I make further more the more revolutionary assertion that these systems, a natural product of integrative patterns and forces in nature, might eventually result in the formation of even higher order systems in which our own anthropological status and identity becomes subordinate to the machinations and patterning of a larger sense of integrative order.

Meta-systems as I have developed this idea applies at multiple levels of natural systems integration, but there is from a developmental standpoint a sense of a grand meta-system that may be the logical, if not quite natural outcome, of further human acculturative development, that is if we do not destroy ourselves in the process. The development of such a grand meta-system will be contingent upon several sets of factors, not the least of which is the improvement of fundamental communications systems and knowledge and information processing systems, as well as the rise of truly automated and integrated artificial systems that can be called in some sense "intelligent" in their behavior. I would now consider such developments not only as inevitable, but as intrinsically benign and therefore entirely desirable and even necessary outcomes if we are to secure a more stable and peaceful world for our human posterity as well as for all other life on earth.

Beyond the rhetoric and hype, and the unfulfilled promises of general systems theory, a systems framework remains critical to the achievement of a truly comprehensive worldview and scientific attitude toward our shared reality, as disillusioned and ideologically non-delusional as we can possibly make this. The potential of general and applied systems theory has largely been unrealized for a variety of reasons, not the least has been the uncoordinated balkanization of the territory of knowledge that comes one way or another under the rubric of systems theory and science. Also, systems thinking and general models have encountered resistance, not so much from specialists hyper-compartmentalized into increasingly focused and narrow problem sets in their respective fields, but because the development of  a truly comprehensive systems framework is probably a threat to the status quo of leaders in the world who want to be able to manipulate and to some extent limit the mind-sets and worldviews of the people they have under their power of control. But even more, the failure of systems thinking, to the extent that it has failed to progress as much as it has promised, stems from those who have or would embrace the meta-paradigm it offers, albeit in a too-general, imprecise, and ultimately irrelevant way. It is simply not sufficient to say that everything coheres into some kind of system at one level or another. It becomes vital to the development of such a perspective to explain in detail not only how that thing coheres to form a part of a system interconnected to other systems, but to study and derive from its behavior predictive generalizations that can be applied, homologically and not just analogically, to other kinds and forms of systems at other levels of the natural integration of reality. 

It is the general patterning that we observe in nature that we identify as being indicative somehow of a natural system. All phenomena, even much that is apparently chaotic, is patterned in meaningful and orderly ways when they are understood in a scientific and systematic manner for what they really are. I would call all of science but aspects of general systems theory and methodology, and there is no scientific problem or question that is not fundamentally a problem or question about systems.

This book is intended as no less than my bible, my compendium, my tome, on general systems thinking and natural and applied systems theory. It is the third of a trilogy of works that began with Natural Systems Theory (2000) and was followed by Meta-systems (2001). This work has been written in bits and pieces, piecemeal, since it was originally planned early in the year 2000. Hence it has been more than three years in the making, and remains to this day basically unfinished in a final form.

I have undertaken to more fully develop comprehensive theories regarding advanced meta-systems science and natural systems theory, attempting to provide natural and logical extensions of these in applied and alternative systems, to operational methodologies, as well as in various theoretical and applied forms and fields of philosophical thought. The term "meta-system" has both metaphoric and operational connotations that must be taken into greater account, and this demands a consideration of the philosophical, ideological and other implications of this line of inquiry in terms of the status and function of knowledge in the world. I have sought thereby to extend the compass, breadth and depth of understanding that natural systems theory and meta-systems science has so far comprehended. I have done so in order to embrace what I would consider to be the complete range and life cycle of knowledge development from original conception and contextualization to application and actualization in real systems.

At the same time, I have sought to articulate the concept and framework of meta-systems in real terms, and to develop thereby a working "meta-system" that can serve as a prototype for the extension of this framework in the world. I have been partially successful in this task. I say partially because of the severely limited resources I've been able to work with, including and especially limited time and human resources. This brings to the foreground though the central dilemma of attempting to bring to realization and concrete expression the meta-systems framework. At all levels and in every facet of meta-systems, there will be a trade-off between means and goals, and these trade-offs are never easily deciphered or calculated because of the enormous complexity that a meta-systems approach tends to. Thus optimal kinds of compromising solutions are always sought, and frequently "invented" that serves as a temporary remedy to the challenges of the articulation of meta-systems.

The applied meta-systems framework as I have developed this is intentionally comprehensive, but in a functional rather than in a formal manner that permits the differentiation and integration of different areas of involvement in a coordinate manner. It is comprehensive in the sense that there is in principle no area of knowledge or human involvement that cannot be defined and nested somewhere within its framework, and thereby automatically establishing a context and integrative network of relations with that area and other meta-system areas. This serves to functionally define all knowledge areas, excluding none, and to integrate these areas into a larger comprehensive framework.

Natural systems theory deals with the scientific conceptioning of how natural systems work. We find nature to be stratified on the basis of size and composite complexity, and within this stratification occur discrete levels of organization that are at least partially determinable by rules that can be stated in the form of a proposition or equation. The natural stratification of reality provides us with a ready system for classification and organization of knowledge in order to understand, in a relative way, how things function in specific terms at specific levels.

Meta-systems science deals with the challenge of the complex integration of reality, and the rise of heterogeneous patterning of super-systems as the result of the interaction of multiple systems at multiple levels. Meta-systems science seeks to employ operational procedures to the description and explanation of this super-complex patterning, as well as to the applied heuristics of this understanding to the creation of alternative systems and the augmentation of reality thereby. Meta-systems science is concerned with both the analysis of data and the synthesis of models relating to naturally occurring problems.

The nature of generalization therefore is different between natural systems theory and meta-systems science. Meta-systems science tends to generalize across to systems models while natural systems theory tends to generalize towards the patterning of natural stratification found in reality. Meta-systems science tends to treat specific problems within a same or similar kind of operational framework, but as unique problems. Natural systems theory is concerned primarily with general problems, or problems of knowledge and understanding of naturally occurring systems that occur at a general level. Specific examples are then said to be experimental tests or demonstrations of the general theory that is in question.

While natural systems theory is more representative of knowledge that is conventionally construed in terms of the traditional scientific disciplines and their emergent sub-disciplines, meta-systems science is a new informational-based science that deals with cross-disciplinary interests and problems arising as the result of the dealing with complexity in systems that stems from several sources and therefore crosses multiple knowledge boundaries.

Both natural systems theory and meta-systems science are primarily concerned with working systems in the natural world, as well as with those working systems that are the product of human imagination and invention. A working system can be defined as any kind of patterned process that maintains regular order over time in a predictable manner. The concept of order is necessary and vital to all of sciences. The universe and physical reality is ordered in certain ways, and appears disordered in other ways. If the universe where totally disordered, then there would be no possibility for science.

As such, natural systems theory and meta-systems science are primarily concerned with the principles of order and disorder that affect different kinds of working systems at different levels of articulation and integration. All working systems are by definition entropy based and inefficient systems as all such systems involve energy exchange that is always less than perfect.

Knowledge is a system, and knowledge was we know it is invariably human knowledge. As such, our knowledge systems are at some point a part of the larger systemic universe, a part of the natural systems that occur in physical reality, and therefore they are not just about such systems. We cannot therefore claim that knowledge systems, if they are to be accurately representative of natural systems, are completely arbitrary or independent or even a priori to the occurrence of any real system, as they are an extension and a part of whatever real system that we seek to understand and learn about. This relationship between knowledge and the world that is known is an important consideration for natural systems theory and meta-systems science, and this consideration extends beyond the problem of anthropological relativity of all human knowledge. In a sense, scientific knowledge represents the manifestation or the expression of the natural order of determinations that govern the behavior of natural systems at all levels and in all ways. It has not been difficult at all to confuse human knowledge, or humanly contrived knowledge, with the factual or natural order of the world. The shape of our worldview is influenced not only by the intrinsic shape of the world but also by the shape of the knowledge that we bring to the construction of that worldview. Natural systems theory and meta-systems science therefore is a part of that knowledge construction, and hence is never a perfect or even sufficient fit with the natural ordering of the world. There is in other words a more general form of relativity of knowledge, of an inherent uncertainty of knowledge, which is basic to and underlies even anthropological relativity or the various forms of physical relativity as these are known or thought to occur. It concerns a fundamental incapacity to know something about the world in any precise or empirically accurate manner with a sense of unquestionably absolute or categorical certainty. The only categorical knowledge forms we know are found in various forms of idealism and in pure mathematics--and these forms are impossible to realize in the world in any absolute or pure manner. We may approximate such forms to the nth degree, but our approximations, if they are to have any real value at all in the world, will always remain essentially just that. What this entails is that science will have no final bottom-line or knowable limit to the advancement of its knowledge, which may at some point no longer proceed by leaps and bounds but by the tiniest fractions of measurement we are capable of achieving.

Knowledge therefore reflects in an intrinsic manner the natural order of things, if we understand how our knowledge systems work. There is nothing magical or mysterious about this isomorphism, as knowledge systems are bound in the same general framework as is any other natural systems. What this tells us is that the advancement of scientific knowledge will proceed in a non-arbitrary and inevitable direction--certain things of a certain kind must be learned or made known through reason, observation and experimentation, before other things can be discovered. It was not unlikely that we should have discovered the processes of nuclear fission and fusion before we discovered the fact that all material on earth is composed of tiny atoms and that every atom has a definite nuclear structure. It was impossible that it could have been the other way around. The progress of scientific knowledge, including its teleological extension to alternative systems development, is inevitable as long as science is practiced in an authentic matter.

Progress in our knowledge, as Kuhn defined it, is not just inevitable, but it is a natural consequence and outcome of the pursuit of such knowledge in the first place, especially by the systematic application of what has commonly come to be called "scientific method." New insight and knowledge is not invented in the imagination, so much as it is discovered through the calculus of reason applied systematically and consistency to the empirical observation of nature. In science, we cannot have multiple alternative theories that explain the function of some natural pattern and all be equal with the same sense of validity. Only one correct theory governs our understanding of the workings of a system or a kind of system upon a certain discrete level--though this knowledge itself might be theoretically embedded in a network of related or interconnected ideas.

Understanding these various aspects of our knowledge, we can predict that certain things will become true in the long run. Scientific knowledge will achieve a natural theoretical integration and unification that will reflect the natural integration of physical reality. As scientific knowledge advances, certain forms of understanding about reality will emerge that are independent of our ability to know or to arbitrarily shape our own knowledge. The discovery of new knowledge through the application of scientific method and praxis will lead also to the further augmentation of reality, or the creation of new real alterative systems, through the scientific based knowledge. This process shall proceed indefinitely into the future, until and unless human beings, through their own actions, or as an unintended consequence of their own actions, destroy themselves and/or the natural world system upon which they depend.

Meta-systems science and natural systems theory therefore comprises what I consider the basis for the theoretical integration and unification of all fields of science and human knowledge in a systematic and coordinate manner. I do not claim that these fields of understanding replace or are substitutes for different disciplines or fields of knowledge. It's main purpose has been to comprehensively complement such knowledge systems, particularly with the notion that development of such systems has led increasingly to hyper-specialization and the consequent hyper-compartmentalization of areas of thought and knowledge into separate areas of activity and interest. At the same time, it is clearly the case that natural systems theory and meta-systems science can bring to bear upon many different fields of study alternative frames of reference and understanding that can provide tremendous heuristic advantages in the acquisition of new knowledge and understanding about reality. Thus they provide there own tools and objectives for the conduct of new research and the application of this research in many areas of study, regardless and alongside of the procedures and research designs that already exist within these areas and that may yet be developed. Thus meta-systems science and natural systems theory are inherently cross-disciplinary and, I would claim, trans-disciplinary knowledge systems that are also complementary to one another. Natural systems science deals with different levels of natural integration of systems in theoretically comprehensive but appropriate terms. Meta-systems science deals primarily with the inter-functioning of systems at multiple levels or between levels that leads to the characterization of real and complex systems that can be said to be heterogeneous in nature.

The development of an advanced systems science that is rooted in natural systems theory and meta-systems science is not about the direct or even metaphorical application of systems theory, especially as this is conventionally construed, to the description of naturally occurring patterns and phenomena. The sense of systems science is rather indirect in the development of alternative theories governing natural systems, and relies upon the use of dynamic and non-linear programming and control structures to model natural systems effectively. The kind of theory this leads to is in a sense a classical form of scientific theory in terms of a set of paradigmatic postulates that can be stated as theorems governing various forms of behavior in natural systems.

Natural systems are exceedingly complex. I believe that in the consideration of metasystems as these are found upon whatever level--say the interaction of the earth's weather patterns with other variables of biological ecology and the changing geophysical distribution of elements on earth. We are thus dealing with a kind of super-complexity that is impossible to resolve or simply in any direct and representative manner.

Super-systems constitute extremely large sets of data with many interacting parts that constitute interdependent variables. It becomes impossible to accurately describe or predict the behavior of all the interacting variables of such systems simultaneously, or even to realistically or accurately portray the behavior of its significant subsystems or components of subsystems.

It is the purpose of natural systems theory and meta-systems science to heuristically model these subsystems and to set empirical criteria of optimum performance standards for the operation of these models. This forms the basis for scientific theory in natural systems science, in which the demonstration of operational models forms the basis for the experimental validation of the theoretical understanding regarding the natural patterning in question. Typically, operational models to test for the optimum performance of theoretical systems are mathematically described and these mathematical models are applied systems. No systems are abstractly perfect except for ideal mathematically systems--all models are approximations of the complexity of reality based upon some criteria of fitness of the model.

In a sense, scientific theory, if correct, sidesteps the issue of actually modeling such systems and replaces this instead with the possibility of conceptually and mathematically defining the fundamental rules of order that govern the normal structural operation of such system. We do not take a frontal approach in systems science to the depiction of systems as systems, as eidetic structures. Rather, we seek through the application of systematic principles to arrive at these general rules of order, either or both conceptually and abstractly in terms of mathematical equations, that serve to predictively summarize the possible eigenvalues or eigenstates that such systems would achieve.

Natural systems are inherently complex and are stratified upon multiple levels of integration. There is a general sense of theoretical relativity regarding such systems such that theory relevant to one level is insufficient to the explanation of any other level of comprehension. We cannot obtain a complete understanding of biological systems only by an exclusive study of physics. At the same time, it is evident that natural systems cohere and are integrated simultaneously upon multiple levels, such that each system is composed of subsystems and in turn becomes part of larger systems. To attempt to describe a higher order system exclusively in terms of lower order functions, while possible, as for instance a complete description of human organic functioning in terms of the biochemical reactions that make up this functioning, without reference to larger organic structures or functions, or without reference to the human organism as a completely integrated system with its own life-trajectory, is to be overly reductivist.

The kind of theoretical generalizations and theoretical system that are developed in reference to one level of natural systems integration, say upon a subatomic level, has nothing directly to do with theoretical explanation on a completely different level, say the community structure of biological populations, or the functioning of the human brain. Theories therefore function largely independently of one another upon their own theoretical levels of articulation. These levels of general articulation of theoretical systems correspond directly to the levels of integration of natural systems.

Furthermore, I have come to the conclusion that with the complexity of natural systems there can be no single comprehensive descriptive theory that serves to account for all variables that affect or influence such a system simultaneously. A field of study like ecology can be said to be meta-scientific in that it attempts to understand the inter-functioning of many complex systems within a larger meta-systemic framework. In other words, such meta-systems, because of their complexity, become meta-logical and meta-theoretic in the sense that they are both empirically and theoretically complex and relative at the same time. Ecology is a clear example of such a cosmographical science that resists theoretical simplification or unification upon a basic or general level. Because the science of ecology is rooted to the study of complex super-systems of nature, its study can be said to be theoretically pluralistic and heterogeneous in structure and character. Geology and Astronomy are other examples of such meta-scientific systems. I do not believe that we can impose upon the study of a field like ecology a single unified theoretical framework that provides a kind of "periodic table" of eco-trophic niches, etc., in other words that provides a systematic accounting of all predictable functioning of ecological systems so described within a single conceptual framework.

We can have unified theories of systems as systems, usually in terms of the components of such systems and their interaction, but we cannot have unified theories of systems of systems, or what can be called super-systems, that embrace different subsystems of different levels of integration and functional organization.

The basis for all relativity of knowledge lies in the uncertainty values that are intrinsic or that can be assigned to such knowledge. It arises from the frame dependency of knowledge, or the dependence of the value attached to knowledge of the frameworks within which such knowledge is perceived, interpreted and used. Alternative frameworks lead to alternative forms of knowledge, as is well known both anthropologically and physically. Within complex systems, there exists no single standard frame of reference to which all cases may equally apply. At this stage, we refer to the complementariness of alternative knowledge frameworks as the basis for the relative uncertainty of our knowledge. We cannot in such contexts assign a specific set of determinations to all known cases. Another way of saying this is that the same event or thing will be observed or known differently, depending upon the framework in which it was observed or made known.

The condition of relativity is intrinsic to all human knowledge. To some extent this is a residual by-product of the fact that all knowledge is essentially human knowledge. There is no knowledge known now that is not constructed by human intelligence for processing by human intelligence. Only with the future discovery of alien intelligence that is differently structured or patterned than our own, will our presupposition of anthropological relativity of human knowledge systems be put to the test. It is likely that any such contact and communication will result in both a major break-down and reorganization of the symbolic organization of human knowledge, as well as in the rapid expansion and extension of this knowledge in completely new ways of integration.

To some extent, science succeeds both by an explicit, objective recognition of this basic sense of anthropological relativity of knowledge, and by the effort to insert some form of objective control over such relativity such that the effects of anthropological relativity upon our knowledge systems are at least minimized if not completely eliminated. We refer to this measure of control objectivity of scientific knowledge, which objectivity is arrived at through inter-subjective criteria of evidentiary witnessing and standardized forms of measurement. Scientific theory achieves success by its predictive and descriptive accuracy, in the long run, and in the larger frame of reference, in a manner that is relatively independent of the human knower that embodies the knowledge. It is likely therefore that scientific knowledge and understanding will provide the common frame of reference for theoretical and meta-scientific understanding that transcends anthropological boundaries and embraces alternative forms of intelligence. A scientifically more advanced civilization than our own will demonstrate greater technological and theoretical sophistication than we possess, and in terms of basic cognitive differentiation theory, will exist in realities that are more differentiated than our own.

The relativity of biological systems is not so apparent to us as is the relativity of physical systems, upon a more basic level, or the relativity of anthropological systems at a higher level of integration. This is possibly because all biological systems exist within a single unified framework and have had a single unitary origin, therefore there is a sense of a central theoretical dogma governing all known biological systems. We do in fact find examples of biological relativity at the level of the species and of the ecosystem and epoch of evolutionary development. Species are unique in time and place and are relative to particular phases of eco-systemic and evolutionary development. This biological relativity results in some degree of headache and equivocation when it comes to the development of exact systems of classification and typology of such systems.

There is only one area of knowledge that can be said to be absolute or non-relativistic, and this is the field of pure theoretical mathematics. Mathematical theory refers to no external reference frames outside of its own theoretical framework. In a sense, it is completely and exclusively abstract. Different forms of ideological or symbolic thought that are closed and internally coherent can also be said to share a measure of this abstract non-relativity. The trouble with these systems are that they are rarely "correct" or true in any larger frame of reference, where as the correct mathematical system can be said to be correct and true in any and every frame of reference.

We apply mathematical theory to our scientific procedures of systematic explanation and description with the hope that such abstract systematization will lend a measure of certainty and stability to natural systems that is otherwise lacking. But the application of mathematics to natural systems entails the attempt to systematically manage and deal with uncertainty in different ways. These procedures tend to be some form of adaptive, linear or dynamic or stochastic control theory. In a sense, our scientific theories of natural systems become essentially the application of specific control theories, and control theory, largely specified in terms of a rule-based system specifying conditional operations and results, constitutes the basis of scientific theory in natural systems science. Control theory in experimental application for optimization really becomes then a form of programming theory that tests alternative criteria systematically for best-fit or closest approximation of results. I believe a field like hard artificial intelligence and cognitive science demonstrates precisely how mathematical models are used for the development of programming control structures for the operational simulation of natural forms of intelligent functioning. When our theories governing the principles underlying certain systems becomes correct, then it is possible to apply these principles systematically, as for instance, in the development of a engine or in the design of an airplane that can accomplish powered flight. Computing at this stage becomes critical to the advanced theoretical and experimental modeling of all complex natural systems.

One caveat must be kept in mind, and that all such programming control structures that predict the theoretical or hypothetical behavior of systems are no better than the conceptual foundations upon which their knowledge is based and integrated. These conceptual foundations are relative to the knowledge framework within which their understanding is defined and constructed. It means that they are relative and are susceptible to the constraints of relative uncertainty that characterizes all human knowledge systems, more or less.

I see meta-systems science and natural systems theory as both the logically and naturally necessary and sufficient conceptual framework for the definition and articulation of the natural and applied sciences and for their theoretical and experimental extension in a coordinate and comprehensive manner to a broad range of related problem areas. I do not see this approach to science as a substitute to the developments of any particular field of science, rather only as complementary to any and every such area. I see the elaboration of these approaches as the basis for the theoretical integration of scientific knowledge, and for all knowledge systems, and therefore as comprising a kind of philosophy of knowledge and science the explication of which becomes also pertinent to its development.