General human algorithm for learning Commonsense

 General human algorithm for learning Commonsense –

Whenever we notice any data, we notice properties of that data upon some reflection. For example, suppose a kid visits your house and sees a big, brown cupboard with books inside it. Say, the “data” he notices in it is – ‘there are books kept inside a cupboard’. (Suppose the cupboard is transparent).

Now, there are an enormous number of properties to this “data”. That, the books are kept on shelves in the cupboard. That, the books are vertical in the cupboard. That, they are touching each other face to face in the cupboard. That some books in the cupboard are red, some blue, some brown. That the books are on 4 layers of shelves of the cupboard. That, the books are inside a door of the cupboard with spherical knobs. Etc.

Notice that these are all properties of the “data” – ‘there are books kept inside a cupboard’.

Now, the kid leaves your house. He goes on with his life. He goes to school, to his tennis coaching, to the playground in his building, eats, sleeps etc.

 

Consider some of the  above properties of the “data” –

1.       books are on shelves in the cupboard,

2.       books are vertical in the cupboard,

3.       books are touching other books in the cupboard,

4.       books are on 4 shelves in the cupboard

Each of these properties get stored in the mind in a “Dual Format” –

Format 1) The whole set of properties associated with the “data”, and

Format 2) Each property, OUT-OF-CONTEXT from the “data”, whereby each becomes one different, general instance of a property of the key words (books, cupboard) in the “data”. Each becomes a data-property piece, wherein this new data now here is the keyword in the original “data”.

Let me explain. Lets see (2) in detail. For example, the 4^th property in the list above – books are on 4 shelves in the cupboard – gets out of context from the “data” and gets stored as a separate instance of “a cupboard having a property that it has 4 shelves”. So now there is an isolated, out of context data-property piece stored in the mind - ‘a cupboard having 4 shelves’.

So now the mind has a list of properties of the “data”, and also, isolated, out of context data-property pieces like ‘a cupboard having 4 shelves’.

 

Lets focus our attention back to (1) – the list/set of properties of the original “data”. When the kid sees another instance (and further, more instances) of the same “data” – ‘books kept inside a cupboard’, firstly, other lists of properties get enlisted in those instances, each for an instance. From across these lists of properties of the various instances of the same “data”, the corresponding properties ((i.e. orientation of the books, the touchability of the books, there being shelves etc.) gather together in the mind (owing to the sheer correspondence) and if the “values” of the properties (like say, the books being ‘VERTICAL’) get repeated across a lot of these instances, a piece of commonsense expectation about the world – that books are kept vertical in cupboards – gets formed in the mind.

Lets extend this to (2). Sometimes the kid might see something like just books on a table, or say in a bag. Here the same above process repeats. Remember, he has an isolated, out-of-context piece like ‘books being vertical’ in his mind. So ‘Books’ (the keyword in the “data”) becomes the new data with a property-value of its being ‘VERTICALNESS’. This will be compared similarly as in the process above, with the values of the orientation of the books seen now (table, bag) and checked for repeated-ness and consequently for the formation of a commonsense expectation about the world. (In this particular case, no particular commonsense will be learned since he sees books on a table being horizontal and vertical in bags. May be something like - books are kept vertically OR horizontally wherever they are.)