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Computer programs have been produced for games such as Chess, Go, Poker, StarCraft 2, Dota. The best ones, Deep Blue and AlphaGo , AlphaZero, Pluribus,... are now considered better than the best human players. More to the point, the computers' game results have been influencing human play.

Apparently, computers are not yet better than human players in Bridge. There can be computer simulations of various hands and hypothetical opposing hands. But what progress have computers made in playing human players in tournaments? Have any new theories of bidding or play evolved as a result of computer-human interaction in Bridge?

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    I understand that to get the results we got for chess/go a lot of commitment/funding is required. Moreover, the prior result from chess/go are not easily translatable to something else, such as bridge. As a result, you might not see the same level of advancement in a bridge computer player until such time some one with the necessary prerequisites takes interest in it. This is not to say this is not possible with the current level of technology. – Andrew Savinykh Mar 3 '20 at 22:29
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    see en.wikipedia.org/wiki/Computer_bridge – Cohensius Mar 4 '20 at 11:06
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    There's a fundamental problem that the rules of bridge are not well-defined for computers. (There are edge cases for this issue in human bridge that also cause controversy.) Specifically, the rules require that partnerships communicate their agreements - including implicit agreements arising from experience playing with their partner - to their opponents. No one has really figured out what it means for a computer to communicate its partnership agreements to other humans or to a different computer program. – Alexander Woo Mar 17 '20 at 1:28
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    @AlexanderWoo: I guess one could publish source code. ;-) Great point that I hadn't thought of. This is particularly pertinent if there is any sort of machine learning programmed in - so that the agreements aren't actually hard-coded anywhere. This might be the base for a really great answer - Computers can't compete fairly against humans in Bridge because they cannot understand the ethical requirements of play, either in regards their human opponents or their partners. – Forget I was ever here Mar 17 '20 at 11:10
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    @AlexanderWoo your comment sounds like a valid answer. Please post it as an answer. – ryanyuyu Mar 20 '20 at 21:40
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There's a fundamental problem that the rules of bridge are not well-defined for computers. Specifically, the rules require that partnerships communicate their agreements - including implicit agreements arising from experience playing with their partner - to their opponents. No one has really figured out what it means for a computer to communicate its partnership agreements to other humans or to a different computer program.

(Note that it does happen in human bridge where one partnership explains their agreements to their opponents, there is misunderstanding, and a director or an appeals committee has to sort everything out, so these rules are not perfectly well-defined for humans either.)

This is less of a problem if the computer is playing a human designed bidding (and carding) system, but a machine-learning designed bidding system could quite possibly (in my opinion would very likely) be incomprehensible to humans.

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    Not just when there's partnerships, but even when it comes to multiple separate players, good AIs are harder to design - that's part of why all the examples given are 2 player games, there's less activity between the AIs turns to calculate based off of (and thus a lot less possible scenarios to evaluate) – Andrew Dec 27 '20 at 4:48
  • The first year Al Levy ran the computer bridge championship, Ginsberg entered GIB playing a wild transfer opening, relay strong club variant (which works better for computers than for humans as computers don't forget). It was very good straight up (for the time), but since the opponents couldn't "understand" it, it got lots of advantage from "incomprehensible bidding". After that (and even now), the allowed system is very restricted. – Mycroft Jan 1 at 17:23

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