Small : Reasoning about Containers : Cognitive and Automated Models

Computers surpass humans in many respects, but remain notoriously poor at common sense reasoning, such as reasoning about every day physical objects. In computers this is generally carried out through the use of step-by-step physical simulation; a computer program is given an exact specification of a physical situation, and the computer calculates the precise trajectory of the system at a sequence of discrete time points. There is good reason, however, to think that human beings may use different techniques -and that the techniques of humans may offer significant advantages over simulation-based calculation. First, humans can make useful qualitative predictions given only partial specifications of the physical and geometrical properties of the situation. Second, humans can make useful qualitative predictions even if they have only a very imperfect knowledge of the physics of the objects or materials involved. Third, humans can predict the qualitative behavior of a complex situation without needing to calculate all the details of the behavior. Finally, humans can use the same physical knowledge for a wide variety of cognitive tasks, including not just prediction but also manipulation, planning design, vision, and text understanding. Our goal is to develop a theory that explains how reasoning with these characteristics can be carried out, both in humans and machines.