Qualitative Reasoning (QR) is an area of research within Artificial Intelligence (AI) that automates reasoning about continuous aspects of the physical world, such as space, time, and quantity, for the purpose of problem solving and planning using qualitative rather than quantitative information.
An example is observing pouring rain and the steadily rising water level of a river, which is sufficient information to take action against possible flooding without knowing the exact water level, the rate of change, or the time the river might flood.
The principles of qualitative reasoning include:[5] The techniques which have been developed for qualitative reasoning permit the simulation of quantitative systems which are subject to multiple constraints in the form of inequalities as well as equalities.
Qualitative reasoning provides a method for modeling with quantitative inequalities in addition to qualities.
Successful application areas include process control, system verification, explanation,[2] autonomous spacecraft support, simulation and explanation of the behavior of structures,[6] failure analysis and on-board diagnosis of vehicle systems, automated generation of control software for photocopiers, conceptual knowledge capture in ecology, and intelligent aids for human learning.