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11

No, GANs are not used. It's reinforcement learning at what it does best. The tree search is an interesting addition and assists with navigating the sheer scale of the game. Although the agent was playing itself to become better, there wasn't 2 separate networks (generator and discriminator). The agent learned through RL and didn't have the error ...


6

Unlikely! Chess has been "solved" by AI much longer than GO (chess engines even before AI are way too strong for human players) and still people are playing and competing. Simply put competition and sports live from the human element. Humans competing against each other will still create the same joy for most people regardless of the fact that all ...


4

OpenAI's Gym is a standardised API, useful for reinforcement learning, applied to a range of interesting environments many of which you can then access for free with little effort. It is very simple to use, and IMO worth learning if you want to practice RL using Python to any depth at all. You could use it to ensure you have good understanding of basic ...


4

AI programs that exist in today's world fall into the category of Narrow Intelligence. Narrow Intelligence are easy to distinguish when compared to General Intelligence (ones that resemble more like humans). Highly advanced AI can often resemble to act like humans thought. I will like to talk about Deep Blue here. Garry Kasparov, in a series of matches ...


4

There are three cases in which it is easily possible to distinguish strong AI play from the strong human play: The AI is playing at superhuman skill level This seems obvious, but I want to mention it for the sake of completeness. The current skill ceiling of top-level chess is well known and an opponent playing way above this skill ceiling must either be ...


4

Go predictions were included in the paper: The experts are far from infallible. They predicted that AI would be better than humans at Go by about 2027. (This was in 2015, remember.) SOURCE: Experts Predict When Artificial Intelligence Will Exceed Human Performance (MIT Tech Review)


3

If you learn a policy or a value function from experience (that is, interaction with an environment), that's RL. In the case of AlphaGo, the MCTS is used to acquire the experience. RL could in fact be considered supervised learning (SL) or, more specifically, self-supervised learning, where the experience corresponds to the labels in SL, especially nowadays ...


3

The branching factor is important, as it limits the effectiveness of search. However, the branching factor in chess is already too high to effectively search without techniques that reduce the size of the search space. Even with millions of tests per second, a computer can only check a small fraction of the possible future games in order to find results in ...


3

Human chess and go experts clearly use evaluation functions. They do come up with moves that look sensible without evaluating the board position, but to validate these candidate moves they evaluate board positions that occur at the end of the variations they calculate. Pretty similar to AlphaGo. Inputting two board states and outputting a preference is a (...


1

Truth be told, I have no idea how to play Go, but luckily this is a AI forum and not a Go forum. Addressing your questions about the specific strategies that AI discovered, there's a paper released by OpenAI titled "Mastering the game of Go without human knowledge" (https://deepmind.com/research/publications/mastering-game-go-without-human-...


1

If you have the best combination of distance between the stones, you should choose the best move to win. In this case, you have to be close to where your opponent plays. It is best to do this by surrounding your opponent's stones. You should always put the first stone in middle or corner of the table.


1

Yes - in chess the term "computer move" is used to denote a move found by a chess engine that a human player would never find (often because they make some slight improvement that a human would not be able to calculate). Humans use pattern recognition and some calculation in order to understand the chess position they are in while computers are able to ...


1

I recall a friend saying that yes, it is somewhat obvious if you are playing against an AI. From what he said, against normal players, there is a certain rhythm and structure that "makes sense". But AI play doesn't have this quality, "it doesn't make sense, but it just works". This seems to echo what you mentioned about the aesthetic quality of Go ...


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