Qualitative Physics is an area of research within AI whose development can be dated back to the late 1970s. As Forbus states in (Forbus 1990):
De Kleer's adds in his cornerstone paper (de Kleer 1984) that the main goals of Qualitative Physics are to "produce causal accounts of physical mechanisms that are easy to understand" and at the same time "be far simpler than the classical physics and yet retain all the important distinctions without invoking the mathematics of continuously varying quantities and differential equations". In other words, the main goal is to develop adequate representations of physical mechanisms that do not involve sophisticated mathematical tools and are understandable by the folk. The main, albeit not the only, inspiration for Qualitative Physics are humans' intuitions about the physical structure of the surrounding world and its aim is to identify the core knowledge behind these intuitions. Humans appear to be using qualitative representation and reasoning about the behaviour of physical environment and our everyday methods differ significantly from the classical physics' view of the world (see (de Kleer 1984)). Given that we are good at functioning in the physical world, it seems reasonable to investigate these methods.