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Basic Orientation will provide two outputs: an aggregate performance score (y_perf) and a score indicating the minimum sustainability (y_sus) according to a set of basic orientor inputs u.

While a system is free to emphasize certain orientors over others (i.e., freedom in the choice of weights according to preferences/strategies), no system can excape the pressures put upon it from its environment and other systems therein. In a much cited report to the Balaton Group Hartmut Bossel [22] identified six basic orientors that will guide a (living) systems' evolution in order to maintain viability [10, p. 185]:

Basic Orientor	Description
EXISTENCE	The system must be compatible with, and able to exist in the normal environmental state. The information, energy, and material inputs necessary to sustain the system must be available.
EFFECTIVENESS	The system should on balance (over the long-term) be effective (not necessarily efficient) in its efforts to secure scarce resources (information, matter, energy) from, and to exert influence on its environment.
FREEDOM OF ACTION	The system must have the ability to cope in various ways with the challanges posed by environmental variety.
SECURITY	The system must be able to protect itself from the detrimental effects of environmental variability, i.e., variable, fluctuating, and unpredictable conditions outside the normal environmental state.
ADAPTABILITY	The system should be able to learn, adapt, and self-organize in order to generate more appropriate responses to challenges posed by environmental change.
COEXISTENCE	The system must be able to modify its behavior to account for behavior and interestes (orientors) of other (actor) systems in its environment.

Each of the six basic dimensions highlights a necessary aspect of viability, that cannot be compensated by a good score in another dimension. Accordingly, the sustainability score according to the inputs for the basic orientors will be aggregated using the min operator. fo further details, see [10, Chapter 4].

Notes

• Bossel additionally points out, that next to environment-determined orientors, there are system-determined orientors (i.e., reproduction, psychological needs, and responsibility). The discussion can be limited to the six orientors from above plus psychological needs for systems containing sentinent beings [10, pp. 185-186].


• It is advisable to work with dimensionless indicator scores on the closed unit interval, where a score of 0 indicates unsustainable performance, while a score of 1 would indicate the best possible performance. (This also conicides with the notion, that all continuous utility functions can be limited to the closed unit interval without loss of generality.)


• The basic orientors have to be operationalized in any real application and a lot of though has to go into finding fitting indicators (which may "load" onto different orientors at the same time). For systems that are made up of subsystems, a subsystem's viability impact upon the total system's viability has to be considered explicitly.

See also

AggregatePerformance, PerformanceIndicator, DmnlInput

weights	Value: ones(nPerf) Type: Real[:] Description: Weights for calculating a weighted average performance score (default = equal weights)
hasSentinentBeings	Value: false Type: Boolean Description: = true, if the system comprises sentinent beings with psychological needs
hasConstantWeights	Value: true Type: Boolean Description: = true, if constant weights are to be used for performance aggregation
func	Value: AggregateFunctions.arithmeticMean Type: AggregateFunctions Description: Function to apply for aggregation (aggregatePerformance.func)