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Decision analysis techniques are advancing as they address more complex issues involving increasing numbers of determinants and as new problems arise in different applications domains. A vital aspect of supporting such innovation is investment in applied research into the development of improved methods. We are advancing developments in two significant areas:
We have remained at the forefront of applied research and development into decision analysis techniques.
Locational-state theory & its applications
This work has advanced so as to contribute to the formulation of a comprehensive system for describing data sets and relationships by applying locational-state theory (LST) and the development of LST applications in the form of locational-state analysis (LSA) as part of a general locational-state method (LSM).
A locational-state file standard
Work is progressing on the development of a standard format for "locational-state files" (*.lsf) which will be supported by a range of server-end scripts designed to manage and audit data, provide appropriate data analysis functions and the standard *.lsf will possess extremely high levels of security through data transformation combined with encryption. We have developed, in collaboration with Navatec, a data transmission format that has been demonstrated to be 30+ times faster that conventional formats including XML. We are also involved in assisting in bench testing the high speed unstructured Plasma Data Base, developed by SEEL and Navatec, founded entirely on LST principles (see Plasma Data Base). The speed of development of this LST frontier has outdated our original standardization aims and we are redefining these under the auspices of the George Boole Foundation so that they reflect the current state of the art technology capabilities.
Analysis of decision-maker and constituency interests
Decision analysis models are made up of relevant relationships (knowledge) between determinants and outputs. In addition to this knowledge base it is also necessary to code decision-maker preferences into the decision analysis model.
There are three broad classes of configuration considered to be decision-maker consituent functions (DMCf) as illustrated in the diagram on the right.
These range from an autonomous DMCf where an individual takes decisions concerning his own affairs with all others remaining unaffected to factional DMCfs where different sized groups of decision makers (boards, committees, government) take decisions on belhalf of constituents to participatory DMCfs where the constuency is involved in all decision making.
Factional and participatory DMCfs are associated with an increasing complexity of decision analysis models. In particular, models needing to satisfy the preferences of increasing sizes of constituencies are known as deference models and these in turn require a careful management of the descriptions and the forms of communication used in the development of decision analysis models involving:
Recent notes, briefs and publciations on our work in these areas can be accessed at the Briefs & publications section of the Decision Analysis Initiative website organized by the George Boole Institute. Access the Decision Analysis Initiative publications section by clicking this link.
1 The ECMA and ISO standard for internet applications, also known as ECMAScript.