fstrick604

Thanks for the reply. Certainly it would be much more complex to do. It would have to have a bidding system as it does now. I wonder though if it could develop bidding judgment by playing and learning from it's mistakes. I don't know. It is interesting. I know I learned systems mostly from books, but judgment mostly from years of playing. Not always good judgment either. One thing I have always struggled to overcome is a fear of doubling because I find it so humiliating to have one wrapped. That should be so easy to overcome, but for me it isn't. I think a robot would do better in that area as they would never be ruled by irrational emotions.

I just read an interesting article in the 10/28 wsj. It seems an app called AlphaGoZero played AlphaGo and beat it 100 games to 0. AlphaGo was programed like GIB I imagine, and it famously beat a top Go expert not long ago. But AlphaGoZero was taught nothing about Go by humans except the rules. It was then made to play 400,000 games against itself and was able to learn the strategy by experience. This is partially how humans learn games, but I had thought computers could not do this yet. Evidently I was wrong. Bridge is different from games like Go and Chess as you don't know where all the pieces are. But my question is could Matt program GIB to learn bridge by playing millions of hands against itself or against humans?

When GIB insisted on a 6-1 fit after I had made a takeout double and later bid my own solid suit several times, I looked more carefully at her understanding of my double. Apparently I had promised 3+ cards in all unbid suits even after I bid my own suit. I like this idea. Has anyone read a system of how to make it playable (how to handle a big one suited hand too strong to overcall in standard methods)?