> If you dislike chess because you don't like abstract total information strategy board games you will not like go
I think that's why I don't like chess. It seems to me that a winning strategy would be to think as far ahead as possible by enumerating all the permutations. A few heuristics exist however.
The neat thing about Go is that, whilst the winning strategy is exactly to think ahead and enumerate all possible positions, to do so is impossible. (Even the superhuman AI fudge it. They can just read farther ahead than humans.)
So to do well you have to learn how to support your reading ahead with heuristics and a feel for the game.
A famous amateur player and advocate for the game once went through all the game records of Go Seigen in order to digitize them. This means having to pore over hand-written diagrams looking for the next number in the sequence of moves. Obviously this is easier if you can guess where to look. But, if you guess them all correctly, then you are playing just as well as the old master! After spending a good few months on the task, he was a significantly better player!
> A famous amateur player and advocate for the game once went through all the game records of Go Seigen in order to digitize them. This means having to pore over hand-written diagrams looking for the next number in the sequence of moves. Obviously this is easier if you can guess where to look. But, if you guess them all correctly, then you are playing just as well as the old master! After spending a good few months on the task, he was a significantly better player!
I'd never heard of this!! Who're you talking about?
Nice. As systems become more and more complicated (like real world itself) it is no longer feasible to enumerate all permutations but rather get a feel for the patterns - an intuition. A skilled intuiter (?) would know the subtle ways in which patterns emerge.
FWIW this isn't a path to success in chess, at least not for a human. There's something like 31 average moves per position in chess. So calculating just 5 moves deep would be 31^10 or about 820 billion positions. In fact even just 2 moves deep would be 31^4 = about a million positions. I'm a relatively strong player and ballparking my speed by playing through the famous Morphy opera house game in my mind - I'm hitting around 2-3 positions per second, in a game I know intimately.
Progress in chess (and I assume Go) is about training your subconscious so that your mind naturally pushes you in the right direction with minimal effort. Think about something like writing. When you're writing something you aren't really thinking through each word in your vocabulary, comparing them, and picking one - it all just kind of flows without you even trying. The same thing happens with chess mastery.
This is why some people say you're not "really" playing chess before a rather high rating. Less experienced players will struggle to simply not leave material hanging. Then as they improve that will no longer be an issue but then they'll still struggle to avoid simple tactical ideas. But once you move comfortably beyond that phase, the game becomes much more about the things people want it to be about - strategy, plans, big picture stuff that's lots of fun. It's one of the way the game draws you in - it gets more and more addictive, and rewarding, the better you become at it!
> If you dislike chess because you don't like abstract total information strategy board games you will not like go
If you think this is equivalent to the description in GP then you are quite simply incorrect.
If you think it's just the actual reason you personally don't like chess, then I'm not sure why you asked in the first place; of course go is an "abstract total information strategy board game".
Yes, in principle such a game has such an algorithm for perfect play. In practice, computers cannot and do not do that for chess (although they make a reasonable approximation) and approach go quite differently (in much the same way that earlier attempts at computer chess did, before Deep Blue's much more brute-force approach proved effective given enough computing power). Getting AI for go to its current superhuman level involved multiple complete revolutions in how the systems were programmed.
Even Connect Four wasn't strongly solved until 1995, and checkers is only weakly solved and that not until 2007 (https://en.wikipedia.org/wiki/Solved_game).