Logico-linguistic modeling is a method for building knowledge-based systems with a learning capability using

conceptual model A conceptual model is a representation of a system. It consists of concepts used to help people knowledge, know, understanding, understand, or simulation, simulate a subject the model represents. In contrast, physical models are physical object su ...

s from

soft systems methodology Soft systems methodology (SSM) is an organised way of thinking and it can be used to tackle general problematic situations that arise in the real world and in the management of change by using action. Developed in England by academics at the Lancast ...

, modal predicate logic, and

logic programming Logic programming is a programming paradigm which is largely based on formal logic. Any program written in a logic programming language is a set of sentences in logical form, expressing facts and rules about some problem domain. Major logic prog ...

languages such as

Prolog Prolog is a logic programming language associated with artificial intelligence and computational linguistics. Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is intended primarily ...

Overview

Logico-linguistic modeling is a six-stage method developed primarily for building

knowledge-based systems A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems i ...

(KBS), but it also has application in manual decision support systems and information source analysis. Logico-linguistic models have a superficial similarity to

John F. Sowa John Florian Sowa (born 1940) is an American computer scientist, an expert in artificial intelligence and computer design, and the inventor of conceptual graphs. Biography Sowa received a BS in mathematics from Massachusetts Institute of Techno ...

's conceptual graphs; both use bubble style diagrams, both are concerned with concepts, both can be expressed in logic and both can be used in artificial intelligence. However, logico-linguistic models are very different in both logical form and in their method of construction. Logico-linguistic modeling was developed in order to solve theoretical problems found in the soft systems method for information system design. The main thrust of the research into has been to show how

(SSM), a method of systems analysis, can be extended into artificial intelligence.

Background

SSM employs three modeling devices i.e. rich pictures, root definitions, and conceptual models of human activity systems. The root definitions and conceptual models are built by stakeholders themselves in an iterative debate organized by a facilitator. The strengths of this method lie, firstly, in its flexibility, the fact that it can address any problem situation, and, secondly, in the fact that the solution belongs to the people in the organization and is not imposed by an outside analyst.Gregory, Frank Hutson and Lau, Sui Pong (1999
Logical Soft Systems Modelling for Information Source Analysis - The Case of Hong Kong Telecom
Journal of the Operational Research Society, vol. 50 (2). Information

requirements analysis In systems engineering and software engineering, requirements analysis focuses on the tasks that determine the needs or conditions to meet the new or altered product or project, taking account of the possibly conflicting requirements of the ...

(IRA) took the basic SSM method a stage further and showed how the conceptual models could be developed into a detailed information system design.Wilson, Brian ''Systems: Concepts, Methodologies and Applications'', John Wiley & Sons Ltd. 1984, 1990. IRA calls for the addition of two modeling devices: "Information Categories", which show the required information inputs and outputs from the activities identified in an expanded conceptual model; and the "Maltese Cross", a matrix which shows the inputs and outputs from the information categories and shows where new information processing procedures are required. A completed Maltese Cross is sufficient for the detailed design of a transaction processing system. The initial impetus to the development of logico-linguistic modeling was a concern with the theoretical problem of how an information system can have a connection to the physical world. This is a problem in both IRA and more established methods (such as SSADM) because none base their information system design on models of the physical world. IRA designs are based on a notional conceptual model and SSADM is based on models of the movement of documents. The solution to these problems provided a formula that was not limited to the design of transaction processing systems but could be used for the design of KBS with learning capability.Gregory, Frank Hutson (1993) SSM for Knowledge Elicitation & Representation, Warwick Business School Research Paper No. 98. Later published in the ''Journal of the Operational Research Society'' (1995) 46, 562-578.

The six stages of logico-linguistic modeling

The logico-linguistic modeling method comprises six stages.

1. Systems analysis

In the first stage logico-linguistic modeling uses SSM for

systems analysis Systems analysis is "the process of studying a procedure or business to identify its goal and purposes and create systems and procedures that will efficiently achieve them". Another view sees system analysis as a problem-solving technique that b ...

. This stage seeks to structure the problem in the client organization by identifying stakeholders, modelling organizational objectives and discussing possible solutions. At this stage it not assumed that a KBS will be a solution and logico-linguistic modeling often produces solutions that do not require a computerized KBS.

Expert systems In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if� ...

tend to capture the expertise, of individuals in different organizations, on the same topic. By contrast a KBS, produced by logico-linguistic modeling, seeks to capture the expertise of individuals in the same organization on different topics. The emphasis is on the elicitation of organizational or group knowledge rather than individual experts. In logico-linguistic modeling the stakeholders become the experts. The end point of this stage is an SSM style conceptual models such as figure 1.

2. Language creation

According to the theory behind logico-linguistic modeling the SSM conceptual model building process is a Wittgensteinian

language-game A language-game (german: Sprachspiel) is a philosophical concept developed by Ludwig Wittgenstein, referring to simple examples of language use and the actions into which the language is woven. Wittgenstein argued that a word or even a sentence h ...

in which the stakeholders build a language to describe the problem situation. The logico-linguistic model expresses this language as a set of definitions, see figure 2.

3. Knowledge elicitation

After the model of the language has been built putative knowledge about the real world can be added by the stakeholders. Traditional SSM conceptual models contain only one logical connective (a necessary condition). In order to represent causal sequences, "

sufficient condition In logic and mathematics, necessity and sufficiency are terms used to describe a conditional or implicational relationship between two statements. For example, in the conditional statement: "If then ", is necessary for , because the truth of ...

s" and "

necessary and sufficient condition In logic and mathematics, necessity and sufficiency are terms used to describe a conditional or implicational relationship between two statements. For example, in the conditional statement: "If then ", is necessary for , because the truth of ...

s" are also required.Gregory, Frank Hutson (1992) Cause, Effect, Efficiency & Soft Systems Models. Warwick Business School Research Paper No. 42. Later published in Journal of the Operational Research Society (1993) 44 (4), pp 149-168 In logico-linguistic modeling this deficiency is remedied by two addition types of connective. The outcome of stage three is an empirical model, see figure 3.

4. Knowledge representation

Modal predicate logic (a combination of

modal logic Modal logic is a collection of formal systems developed to represent statements about necessity and possibility. It plays a major role in philosophy of language, epistemology, metaphysics, and natural language semantics. Modal logics extend other ...

and

predicate logic First-order logic—also known as predicate logic, quantificational logic, and first-order predicate calculus—is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science. First-order logic uses quantifie ...

) is used as the formal method of knowledge representation. The connectives from the language model are logically true (indicated by the "''L''" modal operator) and connective added at the knowledge elicitation stage are possibility true (indicated by the "''M''" modal operator). Before proceeding to stage 5, the models are expressed in logical formulae.

5. Computer code

Formulae in predicate logic translate easily into the

artificial intelligence language. The modality is expressed by two different types of Prolog rules. Rules taken from the language creation stage of model building process are treated as incorrigible. While rules from the knowledge elicitation stage are marked as hypothetical rules. The system is not confined to decision support but has a built in learning capability.

6. Verification

A knowledge based system built using this method verifies itself.

Verification Verify or verification may refer to: General * Verification and validation, in engineering or quality management systems, is the act of reviewing, inspecting or testing, in order to establish and document that a product, service or system meets ...

takes place when the KBS is used by the clients. It is an ongoing process that continues throughout the life of the system. If the stakeholder beliefs about the real world are mistaken this will be brought out by the addition of Prolog facts that conflict with the hypothetical rules. It operates in accordance to the classic principle of

falsifiability Falsifiability is a standard of evaluation of scientific theories and hypotheses that was introduced by the philosopher of science Karl Popper in his book ''The Logic of Scientific Discovery'' (1934). He proposed it as the cornerstone of a sol ...

found in the philosophy of science

Applications

Knowledge-based computer systems

Logico-linguistic modeling has been used to produce fully operational computerized knowledge based systems, such as one for the management of diabetes patients in a hospital out-patients department.

Manual decision support

In other projects the need to move into Prolog was considered unnecessary because the printed logico-linguistic models provided an easy to use guide to decision making. For example, a system for mortgage loan approval

Information source analysis

In some cases a KBS could not be built because the organization did not have all the knowledge needed to support all their activities. In these cases logico-linguistic modeling showed shortcomings in the supply of information and where more was needed. For example, a planning department in a telecoms company

Criticism

While logico-linguistic modeling overcomes the problems found in SSM's transition from conceptual model to computer code, it does so at the expense of increased stakeholder constructed model complexity. The benefits of this complexity are questionable and this modeling method may be much harder to use than other methods. This contention has been exemplified by subsequent research. An attempt by researchers to model buying decisions across twelve companies using logico-linguistic modeling required simplification of the models and removal of the modal elements.Nakswasdi, Suravut (2004
Logical Soft Systems for Modeling Industrial Machinery Buying Decisions in Thailand
Doctor of Business Administration thesis, University of South Australia.