A General Model for Representing Knowledge -Intelligent Systems Using Concepts

Arrow terms of the form have been proposed by Scott and Engeler, 50 years ago, as a model for combinatory logic. Since combinatory logic is Turing-complete, the model causes interest for domains dealing with knowledge, such as artificial intelligence. It has been used to model neural networks – how does the brain think – and connect the notion of computability with observability in natural science. In software testing, arrow terms serve as representation for test cases that allow combination, and thus automated generation of more test cases for testing complex systems. However, knowledge is not a well-defined notion. It is sometimes referred to as awareness of facts or as practical skills and may also refer to familiarity with objects or situations. Knowledge of facts is distinct from opinion or guesswork by virtue of justification. Facts are usually described as a set of conditions, followed by a consequence. This makes the arrow term model an accurate model for knowledge. Knowledge about facts can lead to theories. A theory is knowledge under control. Theories can be approximated by control sequences. The combination of knowledge and theories makes up for intelligent systems.0 Keywords: combinatory logic, arrow term models, artificial intelligence, learning systems, intelligent systems, intuitionism