Hot answers tagged

16

AlphaGo 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.


13

Has the Monte Carlo method already been applied to other games? (Are there concrete implementations available? Yes. This Grad paper might be of interest to you. It covers Backgammon, Bridge, Go, Scrabble, and Clobber. Backgammon, implementation TD-gammon. Bridge, implementation Bridge Barron. Probably outclassed these days by other computer ...


10

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: Keeping Playing Playing is governed by a fairly easily coded set ...


9

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 ...


7

On an 19x19 board there is no computer that evens top level players (9p) as of November 2011. It seems that the strongest programs for the moment use Monte Carlo methods and from time to time matches with pro's are organised, though usually with handicap. The level reached by programs for the last couple of years seems to indicate that they need at least 7 ...


5

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. Note that AlphaGo does not attempt to maximize its ...


4

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 ...


3

First, one needs to understand the differences between Chess and Go from a game complexity standpoint. Next, one must understand the differences between the two types of AI algorithms, and why one works for Chess and the other doesn't. Both chess and Go are perfect information games with no stochastic elements. This means you can always see the full state ...


3

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 ...


2

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 ...


2

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.


2

No, just the total number of placements is far too huge to "solve", and that doesn't even start to take into account movements occurring between placements.


1

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 ...


1

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 ?


1

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


1

Ok, I did a little bit of research. Quoting this paper: In the last few years, several Monte-Carlo based techniques emerged in the field of computer games. They have already been applied successfully to many games, including POKER (Billings et al. 2002) and SCRABBLE (Sheppard 2002). Monte-Carlo Tree Search (MCTS), a Monte-Carlo based technique that ...


1

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, ...


1

To my knowledge, no. I barely know how to play go, but I can speak to the AI side of things a bit. Deep Blue basically uses a big ol' search tree to look many, many moves into the future, like it's testing out numerous parallel games. If a series of moves doesn't terminate in a win or loss, a unit called the "static evaluator" applies a bunch of heuristics ...



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