Introduction
Vagueness of information is an increasing problem in both military and civilian activities. Not only the amount of information in circulation, but the semantic structure and linguistic complexities are challenging the abilities of existing computer systems. Frequently, the actual meaning is lost or distorted. In the military, the need for research and development into developing the accuracy of both weaponry and the intelligence it relies upon is urgent. The US Joint Chiefs of Staff Instructions for 2012 emphasize that while futuristic research is essential, this process may also uncover ideas that could improve how joint forces operate today and could have an immediate impact upon established doctrine. Further the concept must clearly demonstrate “value-added” to current joint doctrine and represent an extant capability.
This note proposes that in the area of computer science, the tool of fuzzy logic would prove a valuable asset in the search for increased precision. Put simply, fuzzy logic as computing with words (CWW from hereon) opens a new way of mechanizing information provided in a natural language, that is, not a machine-generated language as is the general case.
The overall aim of a CWW system is the mechanisation of a proposition or question in a natural language making it computer compatible, a task impossible to achieve using existing number-based computer systems.
Much time and effort is spent upon the development of new technology. However, permeating the use of such technology is “information”. Without information, the unmanned aerial vehicle does not home in upon its target; the intelligence gathered for planning a ground attack is unsafe due to vagueness of meaning or uncertainty as to context. How can this demand be met?
Reducing the Vagueness of Information
Central to human communication and decision-making are words. Each country and culture has its own natural language such as English or French, in comparison to the machine language of 0-1, developed from the classic logic of Aristotle where a proposition is either totally not true or totally true. This form of bivalent logic underpins all Western thought and science to the present day. Historically within the European Enlightenment Leibnitz, the founder of calculus, developed the concept of symbolic logic, where a word is represented by a symbol.
The processing of increasingly large amounts of information requires the use of computer systems. Historically, the development of “smart” technologies demanded a new type of programming logic capable of dealing with vagueness and uncertainty with which the traditional programmes, based upon the classic logic of Aristotle, were insufficient.
Realising this, the system of fuzzy logic was developed in the 1960s by the mathematician and engineer Professor Lotfi Zadeh and later refined by him as Computing With Words. Twelve years ago he described fuzzy logic as a methodology which provides a foundation for a computational theory of perceptions – a theory which will have an important bearing on how human-beings might make perception-based rational decisions in situations of imprecision, uncertainty and partial truth.
During the Second World War, Zadeh’s work was underpinned by advances in computing and communications technology. In an effort to encompass the vagueness and uncertainty of human perceptions he attempted to move from mechanistic computing to humanistic computing, basing his research on the findings of Gödel, who determined the concept of the mathematical set. A set is a collection of things alike in relation to similarity, proximity, colour, or any other attribute. CWW is a system of reasoning and computation in which the objects of reasoning and computation are classes with unsharp boundaries. Zadeh changed the proposition p to p*, a fuzzy set, being a set with unclear boundaries. Such unclear boundaries encompass a wider base of semantic meaning than do mathematical sets.
Professor Zadeh’s work is readily available online and in book form. Although a CWW system may appear complex, it is not difficult to understand and is accessible to those not tutored in higher mathematics.
Comment
In the rapidly expanding domain of information and its communication, two problems continue to challenge the smooth transmission of information. Firstly, that of information overload, where a system becomes congested to the point of system breakdown, and secondly, that of semantic interoperability. Here, several computer systems, frequently in separate countries, attempt to transmit information between themselves without loss of semantic integrity. The larger the amount of information the more it threatens to overload the system and lead to errors of process. One advantage of CWW is the reduction in the amount of information needed for transmission, leading to savings in both time and economics. A further advantage is the fact that CWW makes computing systems accessible to those with little or no computing skills at all, the specific programming being completed by experts in the field
Allied with this, CWW lies at a cross-roads with Information Theory, Knowledge Engineering and Ontology Building and is increasingly seen as a science in its own right. It is of interest to note that Professor Zadeh has recently increased his focus upon the problem of dealing with information. In refining and stressing some of the critical modules in his information models, he strengthens the basic concepts of computing with words into a new frontier in computation. Turning again to the Joint Chiefs of Staff Instructions, it is proposed here that CWW adds value to existing computing systems and opens the door to further cross-disciplinary research and usage, providing increased precision in situations of vagueness and uncertainty of information.
Margaret Cooper, PhD Candidate, University of Surrey
