What is a Reasoning System?

A reasoning system is a software system that generates conclusions from an available knowledge base and uses logical techniques such as deduction and induction. Reasoning systems play an extraordinarily large role in the implementation of Artificial intelligence and in knowledge-based systems. In principle, all existing computer systems are such systems, because they all automate certain types of logic or decisions.

Normally, however, this term is used for systems in which a more complex type of reasoning system is used. For example, systems that implement direct reasoning such as VAT or the customer discount are not considered such systems in the strict sense, but rather systems that make logical inferences about medical diagnoses or mathematical theorems. There are two modes in which reasoning systems operate: interactive mode and batch mode. Both modes can perform the reasoning process with user guidance to determine the best answer.

Types of Reasoning Systems

There are different reasoning systems that have become established in different areas:

Clinical or professional reasoning

In clinical reasoning, the following areas can be distinguished:

  • Scientific Reasoning (SR): subject-specific, profession-specific background knowledge
  • Interactive Reasoning (IR): is in interaction with the other individuals and thinking takes place on the relational level
  • Conditional Reasoning (KR): this concerns ideas about the future and also conditions under which possible futures could occur.
  • Narrative Reasoning (NR): here, thinking takes place in stories and in relation to persons and institutions.
  • Pragmatic Reasoning (PR): the ability to act according to pragmatic considerations.
  • Ethical Reasoning (ER): reasoning determined by attitudes, stances or values.

Case-based Reasoning System

A Case-based Reasoning is case-based reasoning with a case base (case memory) and an imitation of human behaviour, where the solution to a given problem is guided by the solution to a similar and previously solved problem. Case-based reasoning is an approach to modelling human thinking. With this approach, intelligent systems can be built. For this purpose, experiences made (all cases) are stored. These cases are used to solve new tasks. The task classes of CBR systems include the analytical tasks of classification, diagnosis, evaluation, decision support and prediction, as well as the synthetic tasks of configuration, design and planning.

Machine learning systems

Machine learning deals with the computer-based methods for acquiring new knowledge and new skills as well as novel ways of organising existing knowledge. Both symbol-oriented and connectionist methods are understood under the term machine learning. The task of learning systems is to enable the system to perform the set tasks (global or concrete targets) progressively better after repetition than before. The improvement of the system's performance can be achieved by applying new or modified methods and knowledge. The tasks can finally be performed with improved quality (faster, more accurate, safer and more robust).