Now there is AlphaGo by Deep Mind, a company recently bought by Google playing currently a match against 9p Lee Sedol. It is the Deep Blue of Go.
EDIT: The final result of the match of five games was AlphaGo 4 – Lee Sedol 1. This confirms the former conjecture: AlphaGo is the Deep Blue of Go.
I've played literally hundreds of AI's... the strongest opponent cribbage games are all cheating.
The core Issues
Cribbage is focused upon 3 key priorities:
maximize points in hand
maximize points in play
minimize risk of giving points in the crib.
These boil down to two key skills:
Playing is governed by a fairly easily coded set of ...
I would argue that AlphaGo's advantage cannot be significantly attributed to the novelty of its moves.
The original public AlphaGo games were those against Lee Sedol, the second ranked player in the world, in March 2016. At that time, as mentioned, several of AlphaGo's moves were novel, and surprising to Lee Sedol and observers.
Then, after players had had ...
Here's the AlphaGo team's paper that has all of the details (behind a paywall): http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html
I gave a couple of tech talks about this recently.
This one is about how AlphaGo works and the match with Fan Hui 2p: https://www.youtube.com/watch?v=HTDxpxmFRGo
I gave another talk last year about why it's ...
Disclaimer: I have some programming background but haven't ever actually tried to make a Risk AI, so this isn't 100% definitive.
Although making a "perfect" Risk AI might be, it seems like it wouldn't in theory. At the end of the day, Risk is a resource management game, and that's something a computer can do.
For starters, the combat mechanism is fairly ...
The DeepMind channel on Youtube has a short review of each game by Michael Redmond 9P.
At the end of the summary for game 1, Michael estimates that black is slightly ahead on the board. When you factor in the 7.5 point komi, it means that the final score would have been around 5.5 in favor of AlphaGo.
AlphaGo does not attempt to maximize its ...
I wrote the AI engine for BTO Cribbage, a mobile Cribbage app. I played Cribbage growing up and decided to write my own app after playing the other apps. I have played 10+ other apps and most of them stink and/or cheat, like described by @aramis's answer. Being on both sides (a loyal player and an APP creator), I have a different perspective and found the ...
Yes, with Nim being the best-known example
You ask for a strongly solved game (presumably referring to the term in combinatorial game theory). According to Wikipedia, games that are strongly solved
Provide an algorithm that can produce perfect moves from any position, even if mistakes have already been made on one or both sides.
It goes on to note that ...
Yes and no. Every AI will have strategies that it uses, and some will be better than others. The combination of that and how many turns deep you're willing to execute your AI to decide on a move, and how thorough those turns are (do you roll the dice 5 times and branch each time? Or do you use every possible die roll and branch all 40 something times? etc...)...
There is a difference between the two semi-stable double ko positions, although a rather small one. C14 reduces the immediate number of liberties of the G13 leg. This means that black will have a free tempo when G13 runs out of liberties, if we assume that black can find a big enough ko threat to answer the C13 capture with C14 in order to force the B15 gote....
I made an AI agent playing Quoridor. You can play against it right on the browser here: https://gorisanson.github.io/quoridor-ai/. As you can read on the "about" section on the page, I imitated the demonstration model of Daniel Borowski's Quoridor AI (https://danielborowski.github.io/site/quoridor-ai/display.html).
Martijn van Steenbergen's Quoridor program ...
Building a Poker Playing Agent based on Game Logs using Supervised Learning
I found this paper on creating a Hold'em AI that refers to two external log files on page 100 of that paper. One no longer exists. The other, from hhsmithy, costs a couple bucks. They offer logs from various sources, including Poker Stars, Full Tilt Poker and Party Poker.
They also ...
Obviously, AlphaGo is the top AI now. Besides it, a simple way to find information about Computer Go Ranking would be to search for :
Computer go tournament
Here is a list of Go AI from wikipedia
There's a special website called Computer GO that registers past and future tournaments.
There's also a website for KGS Computer Tournaments
According to the ...
No, there is not currently any difficulty settings for the AI.
I cannot find an official source stating this to quote/link as reference, but you can read through the official FAQ and see some mentions of playing against the AI, with no mention of a difficulty setting.
As this is a pretty new implementation of the game, it is constantly in development with ...
W1 should be N11, then black dies, I'd claim from memory.
W1 at R13 is probably not a complete disaster in itself, but O12 should then be O11, or maybe P10 should be O10. That would force black to capture and white would at least build some influence -- not thickness, as she can't protect all cuts.
Even before that, white should probably descend at T13 and ...
AlphaGo relies heavily on Monte-Carlo Tree Search (MCTS), which is a form of decision making that utilizes random choices as an analog for creativity. Specifically, it allows the algorithm to "think" beyond the bounds of it's rational evaluation procedures. (The random choices are subsequently analyzed and weighted in order to determine which random ...
You can download the game record (.sgf) file from this link and use an score estimator as in the KGS Goban (free), which will give you W+2.5 (including komi) and by looking at the screen we can see that AlphaGo could easily got additional points, so perhaps 5.5 as in the previous answer is the best estimate.
State of the art AIs are beating humans, but require more processing power is available on your phone. Here are some good background stories regarding the state of the art:
Chess AIs do really well even with modest ...
The Computer Go Server1 is currently a very active test bed for bots. The Computer Go page at Sensei’s Library refers, under Competitions, to various competitions including the Computer Go Server, with its own page at Sensei’s Library, which gives the URL1. On that site, you will find daily updated tables of bots for 9×9, 13×13 and 19×19, These refer to the ...
This generalization of Tic-Tac-Toe is called m,n,k-game. (the goal is to get k in a row on a (m,n) board).
Some known bounds: (source wikipedia)
(5,5,4) is a draw.
(6,6,5) is a draw.
(7,7,5) and (8,8,5) are draws.
(15,15,5) is a win.
(9,6,6) and (7,7,6) are both draws via pairings.
When the goal is 9 or larger (k>=9) the second player can force a ...
The accepted answer in your linked question is still valid: ELF (the Facebook go bot, account name "ELF") or variants of LeelaZero play on the Kiseido Go Server (usually bots have "LeelaZero" or "LZ" in their names). You can find a list of these bots in the room "Computer Go" (Menu "Rooms" > Room List > Social > Computer Go)
A non-Nim example is one usually presented as a puzzle, such as this Puzzling.SE question. The rules of the game are:
Given a symmetrical (normally circular or square) table, two players take turns putting coins on the table such that no two coins overlap. The player who is first unable to place a coin loses.
There are an infinite number of board ...
AlphaGo plays moves that are "novel," and that is the key to, but not the reason for its success.
The reason that the moves are considered "novel," is that they have been examined and rejected by human players. So then the question is, does Alpha Go's follow up movies (and variations) prove that the moves are sound or not? The almost invariable answer is ...
Xoridor is available as a .jar file that will run wherever you have a Java installed and supports 2 or 4 players.
This version (mentioned in a comment): http://danielborowski.com/quoridor-ai/display.html is the first hit on Google and works in browser but only seems to be two player. I beat it on my first attempt but I'm used to 4 player games. Since the ...
The Chess Master series is arguably capable of doing this. It creates personalities that are defined by their personal valuation of the various pieces. Starting with the standard, rough approximations that are typically used (Queen = 8 points, Rook = 5 points, Bishop = 3 points, etc...), each AI personality has these numbers adjusted, often subtly (down to ...
Agricola from Playdek offer a good challenge. And you can play single or the serie mode against yourself.
Elder Sign , Summon War and Yggdrasil are also good choice.
More depend of the game theme that you like ?
My perspective is having never played Haggis until i played it on the ipad. I have quite a bit of Tichu experience.
The AI offered competition to me for about 5 games. After that i can beat it 4/5 of the time.
So overall i think it is a good way to learn the game, but will not help you get ahead online
I think you would need to know an idle strategy for single player as a baseline (potentially using a variant where you have to keep skulls) since most building games allow you to ignore the other player if you are playing well enough. This makes solo play a great baseline for how to play multiplayer.
If you don't have a good algorithm to figure that out, ...