p.7 Change is the most pervasive characteristic of our time... Change
is never isolated. It is the result of, and it causes, other changes. Change often feeds back on itself. Causal chains
are rarely self-evident and obvious. Even where causalities are known, the human brain is ill-equipped to project the dynamic
consequences... Coping successfully with the challenges of dynamic and interconnected change requires more than anything
else information, and the ability to process this information correctly. It is therefore only natural that due to
their enormous information processing capability, computers are beginning to play their role in assisting man in the performance
of the different tasks of policy analysis. This role will increase... as information must be increasingly applied to using
scarce resources more efficiently
p.7-8 In constant confrontation with the limitations and short-comings
of current tools of computer-assisted policy analysis, the group [of authors contributing to this book],
led by H. Bossel, has focused on three particularly important aspects: (1) the formulation of a theoretical
framework for the description of societal systems and their behavior; (2) the development of interactive (conversational)
instruments of computer-assisted policy analysis; and (3) the simulation of the cognitive/normative processes underlying
all decision-making.
p.11 There can be little doubt that policy analysis and decision-making
concerning the complex issues facing society today stand to benefit from the enormous information processing capability of
the computer - if it is properly used.
p.15 Chapter 6 "Orientors of Nonroutine Behavior"... A set of basic orientors
is derived by different approaches... Its importance lies in the fact that it allows the prediction of likely (rational) system
behavior even under circumstances requiring abrupt qualitative changes in behavioral policy.
p.19 The book is dedicated to those who are children today.
December 1976 Hartmut Bossel [JLJ - I was 10 in December 1976]
[Hartmut Bossel and Edelgard Gruber, Systems Science and Social
Science Foundations of Computer-assisted Policy Analysis, pp.20-78]
p.22 A simulation - like any description of reality - is always a simplified
representation of reality. This image is obtained by a cognitive process representing reality for a certain given purpose,
taking into account certain aspects only, i.e. those seen as relevant for the task. There is no other way to obtain the reduction
of complexity required for the model. As a result, a model is always an image of reality tinged by the subjective point of
view of the model builder... each author - on the basis of his personal experience - may feel he should neglect different
parameters as having only insignificant influence. In addition, one and the same author will model the process differently,
depending on [what] the task calls for
p.23 A conclusion of the philosophy of science is the finding that the validity
of a theory can never be verified, only falsified. At best, a theory can therefore be provisionally valid for lack of falsification.
The same conclusion obviously also applies to simulation models.
p.44 The framework for the simulation of societal systems must be an applicable
systems theory whose structural elements correspond to those of social reality.
[Hartmut Bossel, Computer Models for Policy Analysis: Hierarchy,
Goal Orientation, Scenarios, pp.139-161]
p.139 Computer models are images of reality: as any other
image, they are determined by their object, by point of view, attitude and motivation, by initial knowledge, ability, tools,
and the interest of the model builder concerning the representation and its purposes.
p.139 Today's computer models often resemble the world maps of centuries gone
by: in addition to well-surveyed terrain there exist areas for which only fragmented information is available, and white spots
which are often decorated with phantastic creatures in order to round out the total picture... the main tasks of maps
and computer models as instruments of policy analysis are one and the same: orientation and planning.
p.140 The term "problematique" will here be used in the sense of its usage
by the Club of Rome. "Problematique" therefore means the totality of a long-term societal development whose outcome is uncertain
and potentially dangerous, i.e. which contains crisis potential.
p.142 A correct representation of the interaction between component systems
must be possible, at least in principle.
p.143 The most important function of the computer model is as an instrument
for the study of alternative futures... On the one hand it should be possible for the user to obtain a feeling for the dynamic
behavior of the system, on the other he should be able to conduct precise investigations concerning policy alternatives.
p.143 The model should facilitate the investigation of behavioral alternatives
in user-specified scenarios... it should assist the user in constructing his own internal model of the corresponding segment
of reality.
p.144 The systems analysis of complex systems always requires a reduction
of complexity; the selection of relevant elements and relationships is determined by the point of view of the analyst.
p.150-151 It is instructive to compare other modelling approaches for the
same problem type in the light of the criteria used here... they do not represent an adequate framework for the comprehensive
study of the problematique... the decision making process is seen simply as a preprogrammed stimulus-response-transformation;
despite the fact that by orientation with respect to elementary normative statements this information process may in reality
activate a great number of very different behavioral modes... These models therefore often exhibit a determinism of system
development which simply does not exist in reality... The iterative-dynamic mode of model usage for the interactive development
of strategy is not allowed for. In particular, the orientation of the model user and the transparence of model use both suffer
from restrictions of this mode of model use.
p.151 One should remember, however, that there is no such thing as the Mesarovic-Pestel
World Model. Instead, there exist a number of component models - some of them at a very advanced stage of development - concerning
partial aspects of the global system. For the solution of specific tasks these models are coupled within the framework of
the multilevel approach in a problem-specific manner. However, model components are also often used individually for orientation
and policy analysis concerning limited systems aspects. [JLJ - A great idea. We think in terms of model pieces which
are strategically combined according to the present demands. We might think instead of switching pieces of our model on or
off.]
[Hartmut Bossel, A Modelling Framework for Societal Systems,
pp.162-179]
p.162, 168-170, 173-174 Hypotheses concerning actor and interaction...
Hypothesis 14: In the state analysis, the perceived system state is mapped
onto the multidimensional orientor space of the system to determine the current and future orientor satisfaction state. Comparison
of the orientor satisfaction state with the current and future orientor satisfaction reference state yields the current dissonance
vector containing information on the kind and severity of orientor violations, and, if they can be identified, on the state
of the variables causing the violations...
Hypothesis 15: The perceived state vector and the dissonance vector guide
the policy synthesis process. An attempt at classification of state and dissonance patterns is made first: if applicable response
programs are available, these are applied. If not, then the search for an applicable policy is initiated....
Hypothesis 16: Due to the natural limitations of the processing system, the
policy synthesis process must be guided by heuristic principles and programs (incrementalism, satisficing, mixed-scanning,
etc.). Only rarely can the process be of an optimizing nature...
Hypothesis 17: Trial policies are evaluated for their likely present and future
impact by applying them to an internal model of the environment (including other actors) and of the actor system itself. The
model is normally relatively crude and incomplete and requires constant readjustment through learning...
Hypothesis 24: The results of perception, state analysis, and policy synthesis
are determined to a major degree by the temporal and spatial horizon of the actor systems, i.e. the time horizon as expressed
in (usually fuzzy) future weight functions, and the spatial horizon including other actor systems ("participating systems")
and the domain of the environment whose concerns enter the information processes of the response system.
Hypothesis 25: Quantitative measures of orientor satisfaction... can be established
from physiological/physical and psychological requirements, thresholds and constraints, and from system performance measures
using perturbation analysis of the system... This means that the mapping of the system and environmental state on the orientor
satisfaction state can be made without resource to further subjective assessments, once global indexes have been defined and
chosen on the basis of subjective assessment. [JLJ - powerful theory for creating a computer agent to accomplish a task or
play a game. We see that these hypotheses can be used to orient the future behavior of an actor in an environment, which can
conceivably be accomplished based on the creation of indicators and (initially) the tracking of their values.]
[Orientors of Nonroutine Behavior, Hartmut Bossel, pp.227-265]
p.227 The fact that nonroutine behavior of individual and societal actors
is to a great extent intuitively predictable by other actors - else human interactions would be utter confusion - suggests
that behavioral decisions are oriented with respect to parameters which are shared by, or at least known to, participants
in interactions. We here term these orienting parameters "orientors", in order to avoid some of the connotations commonly
attached to the various types of normative parameters playing a role in the behavior of human actor systems: norms, values,
goals, objectives, attitudes, priorities, preferences, etc., and in order to have a more general label for all of them.
p.227 This report is about the "orientors of nonroutine behavior".
An attempt is made to develop a coherent, albeit at the moment discursive theoretical approach and to deduce
- and empirically validate - a set of "basic orientors", i.e. a set of orienting dimensions guiding the behavior of human
actor systems.
p.227 Orientors are meaningful to a system only if the state of
the system itself, and that of the environment relevant to the system... can be assessed with respect to the orientors. This
requires first that the system perceive the system and environmental state through a set of indicators, i.e. perceived
state variables. The composition of this set may change from moment to moment. It requires second that the perceived system
and environmental state can be mapped on the relevant orientor space. [This] report addresses itself to these questions.
p.230 In non-routine behavior,
- the situation is not familiar to the actor, and
- a suitable response is therefore not available in the memory, but must
be generated ad hoc.
p.232 It is trivial but important to note that meaningful non-routine
behavior (including a trial-and-error approach) can only occur by reference to what have here been called
"orientors": standards, norms, goals, objectives, values, basic needs, etc. The possible successes of unoriented
non-routine behavior can be nothing more but chance successes. Orientors are thus key elements of non-routine
behavior... In routine behavior orientors are not needed, as available response programs are applied without concern
for their consequences.
p.233 the major task of the non-routine decision-making process
is the assessment of actual and projected system states with respect to a set of system orientors... The assessment procedure
then requires... a perceived system state; a set of orientors; a mapping function which takes the perceived system state into
a corresponding orientor state
p.233 Decisions are made and actions are taken upon consideration
of the perceived system state... Those state variables entering into the system's state perception are here termed indicators,
irrespective of whether they are quantifiable or not: Indicators are state variables selected to represent the system and
environmental state... The perception of system and environment is reflected by the choice; while the chosen set of indicators
reciprocally limits the range of perception about the system and its environment... The behavioral response of the
system is therefore conditional on the indicator set: problems not perceived cannot be attacked and solved
p.237 Of primary concern to our discussion will be the decomposition
of the supreme orientor into the dimensions of the basic orientors on the next lower level of the orientor hierarchy.
These are the basic operational dimensions which must - in the given overall system and environmental context - enter the
decision-making process in order to assure satisfaction of the supreme orientor. Basic orientors have dimensions such as:
satisfaction of physical/physiological needs, security, freedom of action, efficiency of control, adaptivity.
p.237 Non-routine decision-making requires orientors for two different functions:
- - to define a reference state for the guidance of decision-making;
- - to evaluate real or projected system states.
p.237 A given actor system can rarely ever make a decision without simultaneously
considering the orientor systems and orientor satisfaction states of other actor systems in addition to his own. [JLJ - this
would be our opponent in a game]
p.240 For our purposes the supreme orientor is much too general to
be of much use. We are interested in the next level of orientors ("basic orientors") which follow from the confrontation of
the supreme orientor with the basic operational capabilities and limitations of the system and the essential characteristics
of the environment. Thus the set of basic orientors derives from the question: "Given the global features of the
system and of its environment, what basic orienting dimensions must the system refer to in its non-routine behavior, and in
particular in fundamental behavioral decisions in order to fulfill the global instruction of the supreme orientor?" [JLJ -
concept applies to checkmate in a game of chess]
p.242 For the operationalization of the concept, it is important to obtain
basic orientors which are
- complete... - irreducible... - each independent of the other orientors in
the set
p.245 The present research owes much in particular to the "basic needs" concept
of Maslow 1954.
p.246 Assume that you can construct a robot which will have the physical and
informational processing capabilities to survive... in an environment containing the resources necessary for its survival,
but in diffuse form.
(1) What systems features would the robot have to possess if it were to survive
as a single individual?
p.251 (1) Application of the supreme orientor to the global characteristics
of the system and of its environment results in a set of basic orientors. All nonroutine systems behavior is oriented directly
or indirectly by reference to this set.
(2) The dimensions describing orientor space (orientor dimensions) at a given
level must be (1) basic (irreducible to even more basic dimensions); (2) complete (all actual dimensions must be represented); [3]
independent (no dimension should be obtainable by combinations of other dimensions).
(3) [JLJ - orientor dimensions identified]
p.253 Basic orientors are the major invariants of systems behavior
and are as such the key to understanding, description, and simulation of systems behavior.
p.253 The behavioral instructions concerning given orientor sets appear to
have two dimensions; one of urgency, and one of satisfaction. In a given situation, attention will first focus on immediate
or pending threshold violations. Once these threats are removed, attention will shift to improving the overall satisfaction
level of the orientor set.
p.263 The analysis presented was based on the hypothesis that non-routine
decisions are made by direct or indirect reference to a set of basic orientors, whose dimensions are identical across human
actor systems, and are probably identical... for all autonomous systems, animate or not, relying for their physical support
on an environment with diffuse resources. [JLJ - This can apply to business or to an agent playing a game, such as chess]
