2. a definition of something, including Intelligence, should be concise, sufficient on its own, without the need for additional explanation of a possible interpretation.
3. the host of intelligence does NOT have to use it wide, the definition should allow to observe (measure, assess) one individual and make a conclusion if the host has or doesn’t have Intelligence (e.g. Turing tests).
4. Intelligence should not depend on a specific field of action; the property/ability/feature called “Intelligence” should be “field-independent”, which makes it “field-universal”, meaning, if it works in one field, it will work any any/every field. The ability to create solutions to problems which have never been solved before is exactly of that type.
Giving a good definition is very important, and not always easy. Take, for example, a famous tale about Plato and Diogenes, which says that “when Plato gave the tongue-in-cheek definition of man as "featherless bipeds," Diogenes plucked a chicken and brought it into Plato's Academy, saying, "Behold! I've brought you a man"” (https://en.wikipedia.org/wiki/Diogenes).
The part which has no name because it goes after the EPILOGUE which is by the definition is the last part of a written piece
The distinct, unique, crucial, necessary and sufficient attribute, feature, property, expression of intelligence is (wait for it) – a DOUBT.
Creating a solution to a problem which have never been solved before inevitably leads to some uncertainties, to the situations when there is no (not exists) purely logical reasoning leading to the answer, to the goal, to the expected result. In this situation an intelligent subject always KNOWS that this is the time when the only possible action is to “go with the gut”, “to flip a coin”. The result – “do this” – is based on fluctuations in the neural network of networks called a brain. This is what no current so called “AI” can do. Current “AI” has no doubts. It makes the decision (“this is this face”, “this is this word”, “this is this …”) based on the training it had. The better its training was, the less mistakes it makes (e.g. looking at a banana and seeing a face). But the current “AI” never doubts its choices; currently an HI (human intelligence) needs to interfere to check “AI”s decisions (if only HI was always smarter than “AI”: https://teachologyforall.blogspot.com/2018/02/Facebook.html).
Until an artificial brain learns how to process fluctuations in its network, artificial intelligence will not be in actual intelligence but merely an efficient recognition device.
5. (the most important distinction between a "game" and "not a game" - like "this is not a game anymore"); a game does not significantly alter the everyday life of the participants, i.e. after the game is finished the participants can return to the pre-game state; the status might be changed, e.g. "a winner", "a loser", but the change in the status does not have a strong effect on the post-game life.
Of course, the meaning of words "significant", "strong" is not defined very well. That is why, in my view, this is not a full definition, conditions 1 - 5 are necessary, but not sufficient, and condition 5 is "fuzzy". But this "pre-definition" would be applicable to the majority of games.