Automating the Abductive Inference Loop

We present a novel approach to handle uncertainty, by assuming an irrational view of the world thus breaking with the tradition of taking a rational view. We propose a solution that handles irrationalities by generating different hypotheses of the environment and testing these for their validity thereby fully automating the abductive loop. By assuming the irrational view, we focus on a fundamental change in relation to existing formal techniques that have been developed over the past decades for dealing with uncertain information. While other methods assume a set of axioms to describe the basic building blocks of the problem domain and use these to build concepts. The new approach, unlike the requirements of a rational system, has no predefined problem domain concepts and any concept can be generated and selected based on their ability to be useful in fulfilling the purpose. This means a completely dynamic ontology is generated and maintained. In this way the proposed system could probably cope with any type of problem domain.