Importance of Commonsense Knowledge in Artificial Intelligence

Importance of Commonsense Knowledge 

There are three reasons for AI to emphasize common-sense knowledge rather than the knowledge contained in scientific theories. 

1) Scientific Theories Represent Compartmentalized Knowledge

In presenting a scientific theory, as well as in developing it, there is a common-sense pre-scientific stage. In this stage, it is decided or just taken for granted what phenomena are to be covered and what is the relation between certain formal terms of the theory and the common-sense world. 

    Thus in classical mechanics it is decided what kinds of bodies and forces are to be used before the differential equations are written down. In probabilistic theories, the sample space is determined. In theories expressed in first order logic, the predicate and function symbols are decided upon. The axiomatic reasoning techniques used in mathematical and logical theories depend on this having been done. However, a robot or computer program with human-level intelligence will have to do this for itself. To use science, common sense is required. 

    Once developed, a scientific theory remains imbedded in common sense. To apply the theory to a specific problem common-sense descriptions must be matched to the terms of the theory. 

For example, d = (1/2)gt² does not in itself identify 'd' as the distance a body falls in time 't' and identify 'g' as the acceleration due to gravity uses the situation calculus discussed in that paper to imbed the above formula, in a formula describing the common-sense situation, for example, 

dropped(x, s) ∧ height(x, s) = h ∧ d= (1/2) gt² ∧ d< h.

    Here x is the falling body, and we are presuming a language in which the functions height, time, etc. are formalized in a way that corresponds to what the English words suggest. s and s' denote situations as discussed in that paper, and F(s, s') asserts that the situation s' is in the future of the situations. 

2) Common-sense Reasoning is Required for Solving Problems in the Common-sense World 

From the problem solving or goal-achieving point of view, the common-sense world is characterized by a different ‘informatic situation, the reasoner doesn't know what facts are relevant to solving his problem. Unanticipated obstacles may arise that involves using parts of his knowledge not previously through to be relevant. 

3) Informal Metatheory of any Scientific Theory has a Common-sense Informatic Character

By this I mean the thinking about structure of the theory in general and the research problems it presents. Mathematicians invented the concept of a group in order to make previously vague parallels between different domains into a precise notion. The thinking about how to do this had a common-sense character. It might be supposed that the common-sense world would admit a conventional scientific theory,  example, a probabilistic theory. But no one has yet developed such a theory, and AI has taken a somewhat different course that involves non-monotonic extensions to the kind of reasoning used in formal scientific theories. This seems likely to work better. 

Research Areas 

Some concepts are fundamental to common sense reasoning. The common sense ontologies are, 

1. Time. 
2. Space. 
3. Materials. 
4. Memory Organization. 

Time 

Here we address notions of time familiar to most people as opposed to the philosophical nature of time. For Instance, 

• Ramesh recorded albums between the mid 1960's and 1970. 
• Ramesh died in 1970. 
• Beautiful People released an album based on samples of all of Ramesh recorded music. 
• We can easily infer that Beautiful People's album was released after 1970. 
• The most basic notion of time is occupied by events, 
• Events occur during intervals - continuous spaces of time. 
• An interval has a start and a end point and duration (of time) between them. 
• Intervals can be related to one another - descriptions such as is-before, is-after, meets, is-met-by, starts, is-started-by, during, contains, ends, is-ended-by and equals. 
• We can build a axiom with intervals to describe events in time. 

Space 

The Blocks World is a simple example of we can model and describe space. However common sense notions such a place object x near object y are not accommodated. Now objects have a spatial extent while events have a temporal extent. So we might try to extend of common sense theory of time. However space is 3D and there are many more relationships than those for time so it is not a good idea.

Another approach is view objects and space at various levels of abstraction. Example, we can view most printed circuit boards as being a 2D object. Choosing a representation means selecting relevant properties at particular levels of granularity. For instance we can define relations over spaces such inside, adjacent etc. We can also define relations for curves, lines, surfaces, planes and volumes. Example: Along, across, perpendicular etc. 

Materials 

We need to describe properties of materials, 

• You cannot walk on water. 
• If you knock a cup of coffee over what happens? 
• If you pour a full kettle into a cup what happens? 
• You can squeeze a sponge but not a brick. 

Liquids (as can be seen from above) provide many Interesting points. It is useful to think of spaces occupied by objects. Thus we can define properties such as, 

• Capacity: A bound to an amount of liquid. 
• Amount: Volume occupied by a liquid. 
• Full: If amount equals capacity. 
• Other properties materials can posses include, 
• Free: If a space is not wholly contained inside another object. 
• Surround: If enclosed by a very thin free space. 
• Rigid. 
• Flexible. 
• Particular: Example, sand